Files

.github/workflows/Tests.yml

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+name: Python Testing CI
+
+on: [push, pull_request]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+          pip install pytest
+
+      - name: Run tests with pytest
+        run: |
+          python -m pytest

api/.dockerignore

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+.github
+.pytest_cache
+__pycache__
+.vscode
+.venv
+build
+JobSelect.egg-info
+test
+feat_to_add.txt
+pytest.ini
+data
+dist
+frontend
+notebooks
+

api/Dockerfile

@@ -0,0 +1,17 @@
+FROM python:3.12-slim
+
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+WORKDIR /Job-Description-Analysis
+
+RUN apt-get update && apt-get install -y --no-install-recommends build-essential && rm -rf /var/lib/apt/lists/*
+
+COPY ./requirements.txt /Job-Description-Analysis/requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . /Job-Description-Analysis
+
+EXPOSE 8080
+
+CMD ["python", "api/JobAnalyze_API.py"]

api/JobAnalyze_API.py

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+"""
+JobAnalyze_API.py - Main API Script
+"""
+ 
+from fastapi import FastAPI, Depends, HTTPException, Security, status
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.security import APIKeyHeader
+from fastapi.responses import JSONResponse
+from fastapi_mcp import FastApiMCP
+from pydantic import BaseModel, field_validator, EmailStr
+from slowapi import Limiter, _rate_limit_exceeded_handler
+from slowapi.util import get_remote_address
+from slowapi.errors import RateLimitExceeded
+from starlette.requests import Request
+from starlette.middleware.base import BaseHTTPMiddleware
+from supabase_auth.errors import AuthApiError
+import hashlib
+import secrets
+import traceback
+import uvicorn
+ 
+from pred import JobAnalyze_6k
+from supabase_client import upsert_api_key_db
+ 
+ALLOWED_ORIGINS = [
+    "https://job-analyzer-view.vercel.app",
+    "http://localhost:5173",
+    "http://localhost:3000",
+]
+ 
+app = FastAPI(title="Unified JobAuto Model API")
+ 
+class ForceCORSMiddleware(BaseHTTPMiddleware):
+    async def dispatch(self, request: Request, call_next):
+        origin = request.headers.get("origin", "")
+        try:
+            response = await call_next(request)
+        except Exception:
+            response = JSONResponse(
+                status_code=500,
+                content={"detail": "Internal server error"},
+            )
+        if origin in ALLOWED_ORIGINS:
+            response.headers["Access-Control-Allow-Origin"]      = origin
+            response.headers["Access-Control-Allow-Credentials"] = "true"
+            response.headers["Access-Control-Allow-Methods"]     = "GET,POST,OPTIONS"
+            response.headers["Access-Control-Allow-Headers"]     = "*"
+        return response
+ 
+app.add_middleware(ForceCORSMiddleware)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=ALLOWED_ORIGINS,
+    allow_credentials=True,
+    allow_methods=["GET", "POST", "OPTIONS"],
+    allow_headers=["*"],
+)
+ 
+API_KEY_NAME   = "JobAnalyze_6k_Key"
+api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)
+API_KEY_DB: dict = {}
+ 
+ 
+def key_func(request: Request) -> str:
+    api_key = request.headers.get(API_KEY_NAME)
+    return api_key if api_key else get_remote_address(request)
+ 
+limiter = Limiter(key_func=key_func)
+app.state.limiter = limiter
+app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler)
+ 
+
+class SignUpRequest(BaseModel):
+    name: str
+    email: EmailStr
+    password: str
+ 
+ 
+class SignInRequest(BaseModel):
+    email: EmailStr
+    password: str
+ 
+ 
+def generate_api(prefix: str = "ja6k") -> str:
+    return f"{prefix}_{secrets.token_hex(32)}"
+ 
+ 
+def hash_key(api_key: str) -> str:
+    return hashlib.sha256(api_key.encode("utf-8")).hexdigest()
+ 
+ 
+async def verify(api_key: str = Security(api_key_header)):
+    if not api_key:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="API Key Missing From Header",
+        )
+    hash_income = hash_key(api_key)
+    db_record   = API_KEY_DB.get(hash_income)
+    if not db_record:
+        try:
+            from supabase_client import get_api_key_db
+            db_record = get_api_key_db(api_key=api_key)
+            if db_record and isinstance(db_record, dict):
+                API_KEY_DB[hash_income] = db_record
+        except Exception:
+            db_record = None
+    if not db_record:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Invalid or Expired API Key, Please get an API Key",
+        )
+    return db_record
+ 
+ 
+class ModelRequest(BaseModel):
+    Job_Desc: str
+    Role: str
+    Type: str
+ 
+    @field_validator("Job_Desc")
+    def jd_not_empty(cls, v):
+        if not v.strip():
+            raise ValueError("Job_Desc cannot be empty")
+        return v.strip()
+ 
+    @field_validator("Role")
+    def role_valid(cls, v):
+        allowed = ["AI Engineer", "AI Developer"]
+        if v not in allowed:
+            raise ValueError(f"Role must be one of {allowed}")
+        return v
+ 
+    @field_validator("Type")
+    def type_valid(cls, v):
+        allowed = ["Internship", "Junior", "Senior"]
+        if v not in allowed:
+            raise ValueError(f"Type must be one of {allowed}")
+        return v
+ 
+ 
+@app.get("/")
+async def main() -> dict:
+    return {"message": "JobAnalyze 6k"}
+ 
+ 
+@app.get("/cron", operation_id="Cron Job")
+async def cron() -> dict:
+    return {"message": "Cron Task Executed"}
+ 
+ 
+@app.post("/auth/create_acc", status_code=status.HTTP_201_CREATED, operation_id="Sign Up")
+async def create_acc(data: SignUpRequest) -> dict:
+    from supabase_client import supabase
+ 
+    email = str(data.email).strip().lower()
+    name  = data.name.strip()
+ 
+    try:
+        res = supabase.auth.sign_up({
+            "email": email,
+            "password": data.password,
+            "options": {"data": {"name": name}},
+        })
+ 
+    except AuthApiError as e:
+        msg = str(e).lower()
+        if "already registered" in msg or "already exists" in msg:
+            raise HTTPException(
+                status_code=status.HTTP_409_CONFLICT,
+                detail="An account with this email already exists. Please sign in.",
+            )
+        if "password" in msg:
+            raise HTTPException(
+                status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+                detail="Password must be at least 6 characters.",
+            )
+        raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e))
+ 
+    except Exception as e:
+        traceback.print_exc()
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="Unexpected signup error — please try again",
+        )
+ 
+    if res.user is None:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Signup failed — Supabase email provider may not be enabled",
+        )
+ 
+    raw    = generate_api()
+    hashed = hash_key(raw)
+ 
+    try:
+        upsert_api_key_db(user_id=hashed, owner=email, api_key=raw)
+    except Exception:
+        traceback.print_exc()
+        return {
+            "message": "Account Created — API key storage failed, contact support",
+            "api_key": raw,
+            "name": name,
+            "email": email,
+        }
+ 
+    return {"message": "Account Created", "api_key": raw, "name": name, "email": email}
+ 
+ 
+@app.post("/auth/sign_in", operation_id="Sign In")
+async def sign_in(data: SignInRequest) -> dict:
+    from supabase_client import supabase, get_api_key_db
+ 
+    email = str(data.email).strip().lower()
+ 
+    try:
+        res = supabase.auth.sign_in_with_password({
+            "email": email,
+            "password": data.password,
+        })
+ 
+    except AuthApiError as e:
+        msg = str(e).lower()
+        if "invalid" in msg or "credentials" in msg or "password" in msg:
+            raise HTTPException(status_code=401, detail="Invalid email or password")
+        raise HTTPException(status_code=400, detail=str(e))
+ 
+    except Exception:
+        traceback.print_exc()
+        raise HTTPException(status_code=500, detail="Unexpected sign-in error")
+ 
+    if res.user is None:
+        raise HTTPException(status_code=401, detail="Invalid email or password")
+ 
+    name   = (res.user.user_metadata or {}).get("name", email.split("@")[0])
+    record = get_api_key_db(owner=email)
+ 
+    if not record:
+        raise HTTPException(status_code=404, detail="API Key does not exist")
+ 
+    return {"email": email, "name": name, "api_key": record["api_key"]}
+ 
+ 
+@app.post("/API/Generate", status_code=status.HTTP_201_CREATED, operation_id="API Key Creator")
+@limiter.limit("5/hour")
+async def create_api(request: Request, email: str) -> dict:
+    raw    = generate_api()
+    hashed = hash_key(raw)
+    API_KEY_DB[hashed] = {"owner": email}
+    upsert_api_key_db(user_id=hashed, owner=email, api_key=raw)
+    return {
+        "owner": email,
+        "api_key": raw,
+        "warning": "Copy this key, this is a one time displayed key",
+    }
+ 
+ 
+@app.post("/JobAnalyze_6k", operation_id="JobAnalyze 6k Model : Analyze Job Descriptions")
+@limiter.limit("10/minute")
+async def JobAnalyze_Pred(
+    request: Request,
+    data: ModelRequest,
+    api_client: dict = Depends(verify),
+) -> dict:
+    resp = JobAnalyze_6k(
+        job_desc=data.Job_Desc,
+        role=data.Role,
+        job_type=data.Type,
+    )
+    return {"answer": [(skill, float(score)) for skill, score in resp]}
+
+mcp = FastApiMCP(
+    app,
+    include_operations=["JobAnalyze 6k Model : Analyze Job Descriptions"],
+    name="JobAnalyze 6k",
+    description="Predicts Most Probable Skills",
+    )
+mcp.mount_http()
+
+if __name__ == "__main__":
+    uvicorn.run("JobAnalyze_API:app", host="0.0.0.0", port=5000)

api/pred.py

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+"""
+pred.py - Powers JobAnalyze 6k model skeleton
+"""
+
+import json
+import pickle
+from typing import List, Tuple
+import numpy as np
+import torch
+from pathlib import Path
+import warnings
+
+warnings.filterwarnings(
+    "ignore",
+    message="InconsistentVersionWarning: Trying to unpickle estimator*",
+)
+warnings.filterwarnings(
+    "ignore",
+    message="Trying to unpickle estimator*",
+) 
+
+
+ROOT = Path(__file__).resolve().parent.parent
+
+from torch import nn
+
+class SkillClassifier(nn.Module):
+    def __init__(self, input_dim, num_labels, hidden_dim=32, dropout=0.3):
+        super().__init__()
+        self.net = nn.Sequential(
+            nn.Linear(input_dim, hidden_dim),
+            nn.ReLU(),
+            nn.Dropout(dropout),
+            nn.Linear(hidden_dim, num_labels),
+        )
+
+    def forward(self, x):
+        return self.net(x)
+
+def JobAnalyze_6k(job_desc: str = "", role: str = "", job_type: str = "", top_k: int = 50) -> List[Tuple[str, float]]:
+    """
+    Predict top-k skills.
+    
+    Current top-k = 48
+    """
+    prep_dir = ROOT / "model" / "prep"
+    if not prep_dir.exists():
+        alt = ROOT / "prep"
+        if alt.exists():
+            prep_dir = alt
+
+    label_path = prep_dir / "label_vocab.json"
+    vector_path = prep_dir / "vectorizer.pkl"
+    weights_path = ROOT / "model_out" / "skill_classifier.pt"
+
+    if not label_path.exists():
+        raise FileNotFoundError(
+            f"Missing {label_path}. Make sure you ran data_prep and model training."
+        )
+    if not vector_path.exists():
+        raise FileNotFoundError(
+            f"Missing {vector_path}. Make sure you ran data_prep."
+        )
+    if not weights_path.exists():
+        raise FileNotFoundError(
+            f"Missing {weights_path}. Make sure you ran model/model.py."
+        )
+
+    with open(label_path, encoding="utf-8") as f:
+        label_vocab = json.load(f)
+    with open(vector_path, "rb") as f:
+        vectorizer = pickle.load(f)
+
+    input_dim = int(getattr(vectorizer, "vocabulary_", {}).__len__()) or vectorizer.transform([""]).shape[1]
+
+    model = SkillClassifier(input_dim, len(label_vocab))
+    model.load_state_dict(torch.load(weights_path, map_location="cpu"))
+
+    model.eval()
+    
+    combined_text = f"{job_desc} {role} {job_type}"
+    X = vectorizer.transform([combined_text]).toarray().astype(np.float32)
+    
+    with torch.no_grad():
+        logits = model(torch.tensor(X))
+        probs = torch.sigmoid(logits).numpy()[0]
+        
+    ranked = sorted(zip(label_vocab, probs), key=lambda x: -x[1])
+    return ranked[:top_k]
+    
+        

api/supabase_client.py

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+"""
+supabase_client.py - Main client for the supabase integration for queries to postgres
+"""
+
+from pathlib import Path
+from dotenv import load_dotenv
+import sys
+import os
+from supabase import create_client, Client
+
+PROJECT_ROOT = Path(__file__).resolve().parent.parent
+if str(PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(PROJECT_ROOT))
+
+_env_path = Path(__file__).resolve().parent / ".env"
+if not _env_path.exists():
+    _env_path = PROJECT_ROOT / ".env"
+load_dotenv(dotenv_path=_env_path)
+
+SUPA_URL = os.getenv("SUPA_URL", "")
+SUPA_KEY = os.getenv("SUPA_KEY", "")
+
+supabase: Client = create_client(SUPA_URL, SUPA_KEY)
+
+def upsert_api_key_db(*, user_id: str, owner: str, api_key: str) -> dict:
+    payload = {"owner": owner, "api_key": api_key}
+
+    resp = (
+        supabase.table("api_tok")
+        .upsert(payload)
+        .execute()
+    )
+    data = getattr(resp, "data", None)
+    return data[0] if data else {}
+
+
+def get_api_key_db(*, owner: str | None = None, api_key: str | None = None) -> dict | None:
+    query = (
+        supabase
+        .table("api_tok")
+        .select("user_id", "owner", "api_key")
+    )
+
+    if owner is not None:
+        query = query.eq("owner", owner)
+
+    elif api_key is not None:
+        query = query.eq("api_key", api_key)
+
+    else:
+        return None
+
+    resp = query.limit(1).execute()
+
+    data = getattr(resp, "data", None) or []
+    return data[0] if data else None
+
+

backups/backup.py

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+"""
+backup.py - Backup client for the table 'api_tok'
+"""
+
+import os
+import requests
+import pandas as pd
+from dotenv import load_dotenv
+load_dotenv()
+
+TABLE_NAME = os.getenv("TABLE_NAME")
+SUPABASE_URL = os.getenv("SUPA_URL")
+SUPABASE_KEY = os.getenv("SUPA_KEY")
+
+def backup_data() -> None:    
+    curr = os.path.dirname(__file__)
+    data_dir = os.path.abspath(os.path.join(curr, "..", "backups/data"))
+    
+    RAW_CSV_PATH = os.path.join(data_dir, "api_tok.csv")
+    
+    API_TABLE_ENDPOINT = f"{SUPABASE_URL}/rest/v1/{TABLE_NAME}"
+    
+    headers = {
+        "apikey": SUPABASE_KEY,
+        "Authorization": f"Bearer {SUPABASE_KEY}",
+        "Content-Type": "application/json",
+    }
+    
+    query = {
+    "select": "*",
+    "order": "user_id.asc" 
+    }
+    
+    api_res = requests.get(API_TABLE_ENDPOINT, headers=headers, params=query)
+    
+    if api_res.status_code == 200:
+        data = api_res.json()
+        pd.DataFrame(data).to_csv(RAW_CSV_PATH, index=False, mode='w')
+        print(f"Backed up api_tok TABLE to {RAW_CSV_PATH}")
+    else :
+        print(f"Failed to backup : {api_res.status_code} - {api_res.text}")
+
+if __name__ == "__main__":
+    backup_data()

backups/sync.py

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+"""
+sync.py - This module is responsible for syncing the local CSV files to the Supabase database.
+Use this to add bulk data from the csv located in the data/ folder to the Supabase tables. 
+This is a one-time utility to populate the database with existing data.
+"""
+
+import pandas as pd
+import requests
+import os
+from dotenv import load_dotenv  
+load_dotenv()
+
+TABLE_NAME = os.getenv("TABLE_NAME")
+SUPABASE_URL = os.getenv("SUPA_URL")
+SUPABASE_KEY = os.getenv("SUPA_KEY")
+
+def sync_api_csv_to_supabase() -> None:
+    df = pd.read_csv('./data/api_tok.csv')
+    print("Synced api_tok CSV to Supabase")
+
+    records = df.to_dict(orient='records')
+
+    headers = {
+        "apikey": SUPABASE_KEY,
+        "Authorization": f"Bearer {SUPABASE_KEY}",
+        "Content-Type": "application/json",
+        "Prefer": "resolution=merge-duplicates"
+    }
+        
+    endpoint = f"{SUPABASE_URL}/rest/v1/{TABLE_NAME}"
+    res = requests.post(endpoint, headers=headers, json=records)
+
+    if res.status_code in [200, 201]:
+        print("Successfully synced data!")
+    else:
+        print(f"Error: {res.status_code} - {res.text}")
+        
+if __name__ == "__main__":
+    sync_api_csv_to_supabase()

cli/api_val.py

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+"""
+api_val.py - Handles the API key prompt. Stores the user-entered key in module-level
+`key` so model_select can read it lazily at inference time.
+"""
+
+from rich import print
+from dotenv import load_dotenv
+from pathlib import Path
+import os
+
+from .utils import clear_console, API_title, query
+
+
+_API_URL = "https://job-description-analysis.onrender.com"
+ 
+_ENV_DIR  = Path.home() / ".jobselect"
+_ENV_FILE = _ENV_DIR / ".env"
+ 
+key: str = ""
+ 
+ 
+def _load_env() -> None:
+    if _ENV_FILE.exists():
+        load_dotenv(dotenv_path=_ENV_FILE, override=False)
+ 
+ 
+def _save_key(api_key: str) -> None:
+    try:
+        _ENV_DIR.mkdir(parents=True, exist_ok=True)
+        _ENV_FILE.write_text(
+            f'JOBSELECT_API_URL="{_API_URL}"\n'
+            f'JOBSELECT_API_KEY="{api_key}"\n',
+            encoding="utf-8",
+        )
+    except OSError as e:
+        print(f"[JobSelect] Warning: could not save key ({e})")
+ 
+ 
+def _load_saved_key() -> str:
+    _load_env()
+    return os.getenv("JOBSELECT_API_KEY", "").strip()
+ 
+def query_api() -> str:
+    clear_console()
+    API_title()
+    query("Which Mode?  \n[yellow]- API : A\n[yellow]- LOCAL : L")
+    mode = input(" >> ").upper()
+    
+    return mode
+ 
+def val_api() -> str:
+    global key
+    
+    mode = query_api()
+    
+    saved = _load_saved_key()
+    if saved and mode == "A":
+        key = saved
+        return key
+    elif mode == "L":
+        key = ""
+        return key 
+    
+    modes = ('A','L')
+    
+    if mode not in modes:
+        mode = query_api()
+              
+    clear_console()
+    API_title()
+    query("Enter API Key (Press Enter to run locally)")
+    typed = input(" >> ").strip()
+    
+    if typed:
+        _save_key(typed)
+        os.environ["JOBSELECT_API_URL"] = _API_URL
+        os.environ["JOBSELECT_API_KEY"] = typed
+        key = typed
+    else:
+        key = ""
+ 
+    return key
+ 
+ 
+def infer_mode() -> str:
+    """Return 'API' or 'LOCAL'. Call after val_api() has run."""
+    if key:
+        return "API"
+    return "LOCAL"

cli/jobselect.py

@@ -0,0 +1,38 @@
+"""
+jobselect.py — CLI entry point.
+Uses relative imports so it works both as an installed pip package
+(jobselect command) and during local development (python -m cli.jobselect).
+"""
+
+from rich import print
+
+from .utils import clear_console, title, query
+from .main_screen import main_screen
+
+
+def cli() -> None:
+    try:
+        jd, role, job_type, results, mode = main_screen()
+
+        clear_console()
+        title()
+
+        mode_colour = "green" if mode == "API" else "cyan"
+        print(f"\n [{mode_colour}][Mode: {mode}][/{mode_colour}]")
+
+        print("\n [yellow]Job Description Provided : \n", jd.strip())
+        print("\n [yellow]Job Role : \n", role)
+        print("\n [yellow]Type : \n", job_type)
+        print()
+
+        print("\n [yellow]TOP Skills \n")
+        for label, prob in results:
+            bar = "█" * int(prob * 30)
+            print(f" {label:25s} {prob:.2f}  {bar}\n")
+
+    except KeyboardInterrupt:
+        print("\n[yellow]Exiting JobSelect")
+ 
+ 
+if __name__ == "__main__":
+    cli()

cli/main_screen.py

@@ -0,0 +1,38 @@
+"""
+main_screen.py - Main screen utils for jobslect CLI tool
+"""
+
+from rich.console import Console
+from rich import print
+
+from .utils import clear_console, title, query
+
+console = Console()
+
+def main_screen():
+    from .api_val import val_api, infer_mode
+
+    val_api()
+    infer = infer_mode()
+
+    clear_console()
+    title()
+
+    print(f"[yellow][JobAnalyze : {infer}]")
+    print("[yellow]>> Welcome to JobSelect!")
+
+    query("Enter Job Description")
+    jd = input(" >> ")
+
+    query("Enter Role  (AI Engineer / AI Developer)")
+    role = input(" >> ")
+
+    query("Enter Type  (Internship / Junior / Senior)")
+    job_type = input(" >> ")
+
+    from .model_select import predict
+
+    with console.status("[bold green]Loading...", spinner="dots2"):
+        results, mode = predict(jd, role=role, job_type=job_type, force_local=(infer == "LOCAL"))
+
+    return jd, role, job_type, results, mode

cli/model_select.py

@@ -0,0 +1,93 @@
+"""
+model_select.py — inference routing (API first, local fallback).
+Never prompts the user. Key is resolved lazily at predict() call time.
+"""
+
+from pathlib import Path
+from dotenv import load_dotenv
+from rich import print
+import os
+import requests
+import sys
+ 
+ 
+def _load_env() -> None:
+    candidates = [
+        Path.cwd() / ".env",                                    
+        Path.home() / ".jobselect" / ".env",                    
+        Path(__file__).resolve().parent.parent / ".env",        
+    ]
+    for path in candidates:
+        if path.exists():
+            load_dotenv(dotenv_path=path, override=False)
+            return
+ 
+ 
+def _resolve_config() -> tuple[str, str]:
+    _load_env()
+    url = os.getenv("JOBSELECT_API_URL", "").strip().rstrip("/")
+    key = os.getenv("JOBSELECT_API_KEY", "").strip()
+    return url, key
+ 
+ 
+def _resolve_key(env_key: str) -> str:
+    try:
+        from . import api_val
+        if api_val.key:
+            return api_val.key
+    except ImportError:
+        try:
+            import api_val  
+            if api_val.key:
+                return api_val.key
+        except ImportError:
+            pass
+    return env_key
+ 
+ 
+def _local_predict(jd: str, role: str, job_type: str):
+    PROJECT_ROOT = Path(__file__).resolve().parent.parent
+    if str(PROJECT_ROOT) not in sys.path:
+        sys.path.insert(0, str(PROJECT_ROOT))
+    from model.pred import JobAnalyze_6k as _job_analyze
+    return _job_analyze(jd, role=role, job_type=job_type)
+ 
+ 
+def _call_api(
+    jd: str, role: str, job_type: str, api_key: str, api_url: str
+) -> list[tuple[str, float]]:
+    endpoint = f"{api_url}/JobAnalyze_6k"
+    headers  = {"JobAnalyze_6k_Key": api_key}
+    payload  = {"Job_Desc": jd, "Role": role, "Type": job_type}
+ 
+    response = requests.post(endpoint, json=payload, headers=headers, timeout=(10, 120))
+    response.raise_for_status()
+ 
+    data = response.json()
+    return [(skill, float(score)) for skill, score in data["answer"]]
+ 
+ 
+def predict(jd: str, role: str, job_type: str, force_local: bool = False) -> tuple[list[tuple[str, float]], str]:
+    if force_local:
+        results = _local_predict(jd, role=role, job_type=job_type)
+        return results, "LOCAL"
+
+    api_url, env_key = _resolve_config()
+    api_key = _resolve_key(env_key)
+
+    if api_url and api_key:
+        try:
+            results = _call_api(jd, role, job_type, api_key, api_url)
+            return results, "API"
+        except requests.exceptions.ConnectionError as e:
+            print(f"[red][JobSelect] Connection error: {e} — falling back to LOCAL")
+        except requests.exceptions.Timeout:
+            print("[red][JobSelect] Request timed out/Under Maintainance — falling back to LOCAL")
+        except requests.exceptions.HTTPError as e:
+            code = e.response.status_code if e.response is not None else "?"
+            print(f"[red][JobSelect] API error {code} — falling back to LOCAL")
+        except Exception as e:
+            print(f"[red][JobSelect] Unexpected error: {e} — falling back to LOCAL")
+ 
+    results = _local_predict(jd, role=role, job_type=job_type)
+    return results, "LOCAL"

cli/utils.py

@@ -0,0 +1,41 @@
+"""
+utils.py - Main Utilities for the CLI Interface
+"""
+
+import os
+import subprocess
+from pyfiglet import Figlet
+from rich import print
+from rich.console import Console
+
+console = Console()
+
+def clear_console() -> None:
+    if os.name == "nt":
+        subprocess.run("cls", shell=True)
+    else:
+        subprocess.run(["clear"])
+
+
+def API_title() -> None:
+    f = Figlet(font="slant")
+    print("——————————————————————————————————————————————————————————————————————")
+    print(f.renderText("JobSelect CLI"))
+    print("           Copyright Akshay Babu, All rights reserved")
+    print("——————————————————————————————————————————————————————————————————————")
+
+
+def title() -> None:
+    f = Figlet(font="slant")
+    print("——————————————————————————————————————————————————————————————————————")
+    print(f.renderText("JobSelect CLI"))
+    print("[blue]               Running Model : JobAnalyze 6k v1.0")
+    print("           Copyright Akshay Babu, All rights reserved")
+    print("——————————————————————————————————————————————————————————————————————")
+
+
+def query(message: str) -> None:
+    print("\n[yellow][JobSelect]")
+    print(f"[yellow] >> {message} : ")
+    print("[You]")
+    

frontend/data/clean/cleaned_job_descriptions_internships.csv

@@ -0,0 +1,660 @@
+id,role,type,job_desc,year,qualification,experience,tech_skills,soft_skills
+1,AI Engineer,Internship,"Final year students / recent graduates in CS, AI, Data Science, or related fields
+Strong Python programming skills
+Understanding of Machine Learning / Deep Learning fundamentals
+Exposure to LangChain, Hugging Face, OpenAI APIs, or similar tools
+Curiosity, ownership mindset, and willingness to learn fast
+Strong problem-solving skills",2026,Bachelors,0,"Python, ML, LangChain, Hugging Face, OpenAI API","Communication, Problem Solving"
+2,AI Engineer,Internship,"Proficiency in Python and comfort working with APIs (REST, JSON, authentication).
+Working understanding of Large Language Models (LLMs) and prompt engineering - gained through coursework, online learning, personal projects, hackathons, or open-source contributions.
+Familiarity with at least one agent or LLM framework (e.g., LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, the Anthropic /OpenAI SDKs, or the Model Context Protocol).
+Strong problem-solving skills and the ability to break ambiguous business problems into structured, automatable steps.
+Excellent communication skills and ability to work collaboratively with others.
+Experience with vector databases and Retrieval-Augmented Generation (RAG), Exposure to tool use / function calling, multi-agent orchestration, or workflow automation tools (e.g., n8n, Zapier), SQL and PowerBI, Awareness of evaluation, guardrails, or safety practices for LLM applications are good to have. B Tech / B.E. in Computer Science, Information Technology, or a similar field. Candidates from other engineering or science backgrounds with demonstrated hands-on experience building with LLMs or AI agents are also encouraged to apply.",2026,Bachelors,0,"Python, APIs, LLMs, Prompt Engineering, LangChain, LangGraph, CrewAI, AutoGen, MCP, VectorDB, n8n, RAG","Communication, Problem Solving"
+3,AI Engineer,Internship,"Strong interest in AI and a willingness to learn and explore GenAI tools and frameworks.
+Programming skills in languages such as Python, JavaScript (React, Angular, Express.js, Node.js, NextJS), or similar.
+Front-end and Back-end engineers are welcome; Full-Stack developers are preferred.
+Excellent problem-solving skills and ability to work in a collaborative environment.
+Strong communication skills, both written and verbal.
+Frontend: Ability to use asynchronous API calls in React via fetch or axios to make HTTP requests to an LLM API endpoint.
+Frontend: Ability to consider user interactions when interacting with a model and guide users accordingly
+Backend - Understanding of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).
+Backend/Frontend - API integration - Familiarity with REST, GraphQL, or gRPC.
+Data Scientist = Familiarity with data pipelines: Ingestion, Cleaning/preprocessing, Transformation/Feature Engineering, Model Training/Evaluation, Model Deploying/Serving and Monitoring/Maintenance",2026,Bachelors,0,"Python, Javascript, React, Full Stack, APIs, ML, TesnorFlow/Pytorch, Ingestion, Data Cleaning, Feature Engineering, Model Training, Model Evaluation, Model Deploying, Model Maintenance, GenAI","Communication, Problem Solving"
+9,AI Engineer,Internship,"Python
+Machine Learning Fundamentals
+Large Language Models (LLMs)
+Prompt Engineering
+APIs & Integrations
+OpenAI APIs
+LangChain
+RAG Systems
+Vector Databases
+Hugging Face
+TensorFlow
+PyTorch",2026,Bachelors,0,"Python, ML, LLMs, Prompt Engineering, APIs, LangChain, RAG, VectorDB, Hugging Face, TensorFlow/PyTorch","Communication, Problem Solving"
+10,AI Engineer,Internship,"Solid understanding of LLMs, tokenization, transformers.
+Python programming (Pandas, NumPy, Hugging Face, LangChain, etc.).
+Exposure to AWS services like EC2, Lambda, S3, or SageMaker.
+Eagerness to explore real-world AI use cases (agents, copilots, RAG).
+Basic ML knowledge and hands-on project experience.
+Experience with serverless deployments on AWS.
+Familiarity with monitoring and logging (e.g., CloudWatch, OpenTelemetry).
+Contributions to open-source AI tools or model",2026,Bachelors,0,"Python, Pandas, NumPyHugging Face, LangChain, AWS, Agents, RAG","Communication, Problem Solving"
+13,AI Developer,Internship,"Basic to intermediate Python programming skills.
+Understanding of AI/ML, Generative AI, and Prompt Engineering.
+Familiarity with APIs, databases, and version control (Git).
+Strong analytical, problem-solving, and communication skills.
+Exposure to LangChain, RAG, Vector Databases, AI Chatbots, or related projects.
+Knowledge of AWS, Azure, or Google Cloud is a plus\",2026,Bachelors,0,"Python, ML, GenAI, APIs, Git, Prompt Engineering, LangChain, RAG, VectorDB, AWS/Azure","Communication, Problem Solving, Analytical Skills"
+27,AI Engineer,Internship,"Python Skills: You should be very comfortable with Python and async programming.
+LLM Experience: You have used APIs from OpenAI, Anthropic, or Gemini to build more than just a simple chatbot.
+Agent Knowledge: You understand how to give an AI tools (functions) to call so it can perform real tasks.
+Vector Databases: Basic experience with Pinecone, FAISS, or similar tools for searching through product data.
+You have used LangGraph, CrewAI, or AutoGen before.
+You understand RAG (Retrieval-Augmented Generation).
+You can build simple frontends in React or Next.js to show off your AI tools. 
+",2026,Bachelors,0,"Python, Javascript, React, LLMs, VectorDB, LangGraph, CrewAI, AutoGen, RAG","Communication, Problem Solving"
+28,AI Engineer,Internship,"Exposure to Full-Stack Development (frontend and backend technologies).
+Experience working with or building projects using AI technologies and Large Language Models (LLMs).
+Familiarity with modern web development frameworks and APIs.
+Understanding of software development best practices.
+Experience with Git and collaborative development workflows
+Strong interest in AI and emerging technologies.
+Positive attitude and a proactive, can-do mindset.
+Strong problem-solving and analytical skills.
+Ability to work independently in a remote environment.
+Excellent communication and collaboration skills.
+Eagerness to learn, experiment, and take ownership of projects.
+Experience with OpenAI, Anthropic, or other LLM platforms.
+Knowledge of vector databases, RAG systems, or AI agents.
+Experience deploying applications to cloud platforms.
+Previous internship, academic, or personal projects involving AI products. ",2026,Bachelors,0,"Python, Git, Github, Full Stack, LLMs, APIs, GenAI, VectorDB, RAG, AWS/Azure","Communication, Problem Solving, Analytical Skills"
+29,AI Engineer,Internship,"Python, TensorFlow, PyTorch, Scikit-learn, NumPy, pandas, Git, C#, .NET, R, Deep Learning, LLMs ",2026,Bachelors,0,"Python, TensorFlow/PyTorch, Scikit-Learn, NumPy, Pandas, Git, C#, .NET, R, ML, LLMs ","Communication, Problem Solving"
+30,AI Engineer,Internship,"Recently completed a degree in Computer Science, AI, ML, Data Science, or related fields
+Strong understanding of Generative AI and LLM fundamentals
+Proficiency in Python
+Experience or familiarity with:
+RAG architectures
+Prompt engineering
+Vector databases (FAISS, Pinecone, Chroma, etc.)
+Good problem-solving and analytical skills
+Tools & Technologies (Exposure to Any Is a Plus)
+LangGraph for agent workflows
+Strands or similar agent frameworks
+A2A (Agent-to-Agent) protocols
+LLM frameworks such as LangChain
+OpenAI / open-source LLMs
+REST APIs and JSON-based integrations
+Experience building AI agents or copilots
+Knowledge of NLP, embeddings, and semantic search
+Familiarity with cloud platforms or deployment workflows
+Prior hands-on projects in Generative AI or agent-based systems
+",2026,Bachelors,0,"Python, GenAI, LLMs, RAG, Prompt Engineering, VectorDB, LangChain, LangGraph, APIs, NLP","Communication, Problem Solving, Analytical Skills"
+38,AI Engineer,Internship,"Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field
+Foundational knowledge of machine learning concepts, statistical modeling, and data structures
+Proficiency in Python and familiarity with ML libraries such as PyTorch or TensorFlow
+Experience with data preprocessing and dataset management
+Strong analytical and problem-solving skills
+Clear written and verbal communication skills in English
+Ability to work independently in a remote environment while meeting deadlines
+Prior experience contributing to AI/ML research projects or open-source repositories
+Familiarity with hybrid AI approaches, generative models, or symbolic AI
+Experience with version control (Git) and collaborative development workflows ",2026,Bachelors,0,"Python, ML, TensorFlow/Pytorch, GenAI, Git, Github","Communication, Problem Solving"
+39,AI Engineer,Internship,"• B.Tech, MCA, MSc, BSc, BCA, M.Tech students or graduates
+• Basic knowledge of Python preferred
+• Strong interest in AI and Data Science
+• Willingness to work on real-world projects 
+• Advanced Python
+• Machine Learning Practical Knowledge
+• Data Analysis Project Knowledge
+• Basic Knowledge of AI Concepts including Gen AI/LLM Cloud Deployment 
+",2026,Bachelors,0,"Python, ML, GenAI, LLMs","Communication, Problem Solving"
+40,AI Engineer,Internship,"• Final year students / recent graduates in CS, AI, Data Science, or related fields
+• Strong Python programming skills
+• Understanding of Machine Learning / Deep Learning fundamentals
+• Exposure to LangChain, Hugging Face, OpenAI APIs, or similar tools
+• Curiosity, ownership mindset, and willingness to learn fast
+• Strong problem-solving skills 
+",2026,Bachelors,0,"Python, ML, LangChain, Hugging Face, APIs","Communication, Problem Solving"
+41,AI Engineer,Internship,"Solid understanding of LLMs, tokenization, transformers.
+Python programming (Pandas, NumPy, Hugging Face, LangChain, etc.).
+Exposure to AWS services like EC2, Lambda, S3, or SageMaker.
+Eagerness to explore real-world AI use cases (agents, copilots, RAG).
+Basic ML knowledge and hands-on project experience.
+Experience with serverless deployments on AWS.
+Familiarity with monitoring and logging (e.g., CloudWatch, OpenTelemetry).
+Contributions to open-source AI tools or models 
+",2026,Bachelors,0,"Python, Pandas, NumPy, Hugging Face, LangChain, AWS/Azure, RAG, ML ","Communication, Problem Solving"
+46,AI Engineer,Internship,"1. Design, build, and optimize scalable Agentic RAG (Retrieval-Augmented Generation)
+pipelines for complex data environments.
+2. Develop and implement Agentic AI workflows to automate multi-step reasoning and
+decision-making tasks.
+3. Assist in deploying, running, and fine-tuning local Large Language Models (LLMs) on
+dedicated hardware to optimize for speed and accuracy.
+4. Work with vector databases and embedding models to improve data retrieval
+mechanisms.
+5. Write scalable, maintainable, and well-documented code to support AI infrastructure.
+6. Collaborate with backend engineers to seamlessly integrate AI agents and LLM 
+Python, Machine Learning, Artificial intelligence and LLM evaluation",2026,Bachelors,0,"Python, RAG, LLMs, ML, ","Communication, Problem Solving"
+47,AI Engineer,Internship,"• Perform data collection, cleaning, preprocessing, and exploratory analysis on structured and unstructured datasets.
+• Implement algorithms for supervised, unsupervised, and deep learning under mentor guidance.
+• Conduct experiments, tune hyperparameters, and document results clearly and accurately.
+• Support deployment of models through APIs, pipelines, or cloud platforms.
+• Research emerging AI/ML techniques and contribute insights to ongoing projects.
+• Collaborate with engineering, data, and business teams to translate requirements into solutions.
+• Write clean, efficient, and well-documented code following best practices.
+• Create visualizations, reports, and presentations to communicate findings.
+• Participate in code reviews, sprint meetings, and technical discussions.
+• Currently pursuing a degree in Computer Science, Data Science, AI, or related field.
+• Strong fundamentals in statistics, linear algebra, and probability concepts.
+• Hands-on experience with Python, SQL, and ML frameworks such as TensorFlow or PyTorch.
+• Curious, analytical, self-driven, and eager to learn fast in a dynamic environment. ",2026,Bachelors,0,"Python, ML, APIs, SQL, TensorFlow/PyTorch, ","Communication, Problem Solving, Analytical Skills"
+48,AI Engineer,Internship,"1. Work across AI automation, full-stack development, and AI/ML tasks based on project requirements and individual core strengths.
+2. Build automation workflows using Make.com and n8n for end-to-end system integration.
+3. Integrate APIs including CRMs, email systems, WhatsApp platforms, and advertising tools into automated workflows.
+4. Develop and maintain web applications using React for frontend development and FastAPI or Node.js for backend systems.
+5. Manage and work with databases such as PostgreSQL and MongoDB.
+6. Build, integrate, and deploy LLM-based solutions including chatbots, RAG pipelines, and AI agents.
+7. Utilize OpenAI, Claude APIs, and LangChain for AI-driven product development.
+8. Work with Python for AI/ML tasks including prompt engineering, fine-tuning, and model integration.
+9. Deploy projects on cloud platforms such as Vercel, AWS, and GCP.
+10. Debug technical issues and maintain clean, well-documented codebases.
+11. Research emerging AI tools and recommend suitable solutions for client and internal use cases.
+• are available for full time (in-office) internship
+• can start the internship between 28th May'26 and 2nd Jul'26
+• are available for duration of 4 months
+• have relevant skills and interests
+• are Computer Science Engineering students
+Python, SQL, Machine Learning, Neural Networks, Deep Learning, Artificial intelligence, APIs and Vibe Coding
+• 1. Strong expertise in at least one area such as AI automation using Make.com or n8n, full-stack development with React and backend technologies, or AI/ML using Python, LLMs, and RAG systems is preferred.
+• 2. Willingness to learn and work across multiple technical domains is important.
+• 3. Hands-on experience with APIs, webhooks, and JSON is desirable.
+• 4. A portfolio or GitHub profile showcasing real-world projects will be strongly preferred.
+• 5. Familiarity with AI tools such as ChatGPT, Claude, and LangChain is valued.
+• 6. A fast-execution and builder-oriented mindset is appreciated.",2026,Bachelors,0,"Python, APIs, ML, n8n, React, SQL, AWS/Azure, RAG, LLMs, Github, LangChain","Communication, Problem Solving"
+49,AI Developer,Internship,"1. Building event-driven automations to capture notifications, web-hooks, emails, messages, and CRM events, and routing them to LLMs for contextual responses.
+2. Designing and deploying AI agents using Power Automate ( Desktop), Make.com, Zapier, OpenAI Assistants API etc.
+3. Implementing multi-agent workflows for various applications needs like lead qualification, follow-ups, marketing content for social media, etc.
+4. Enabling cross-platform messaging automation across WhatsApp, LinkedIn, email, and CRM systems with full context retention.
+5. Producing high-quality Instagram Reels and YouTube videos that showcase products, workflows, and AI-driven use cases.
+Logical reasoning, Problem Solving, Automation, APIs, Generative AI Tools, ChatGPT, LLMOps, AI Video Generation and AI Image Generation
+• 1. Automation and workflow design with strong logical reasoning and test automation skills.
+• 2. Experience with Power Automate.
+• 3. Working knowledge of n8n, Make.com, Zapier, and similar automation platforms.
+• 4. Experience building and managing AI agents and LLMs.
+• 5. Understanding of LLM evaluation and response quality optimization.
+• 6. Proficiency in Python for automation and integrations.
+• 7. Strong understanding of APIs, JSON, and webhooks.
+• 8. Basic knowledge of web development fundamentals.
+• 9. Proficiency in Adobe Illustrator, Photoshop, and Canva.
+• 10. Ability to create photorealistic mockups with accurate lighting, textures, and perspective.
+• 11. Understanding of motion design basics using tools like After Effects.
+• 12. Experience with AI image generation tools
+• 13. Experience with AI video generation tools ",2026,Bachelors,0,"Python, LLMs, ML, APIs, n8n, GenAI","Communication, Problem Solving"
+50,AI Developer,Internship,"• Currently pursuing a bachelor's or master's degree in computer science with a strong interest or focus on Generative AI and/or Machine Learning
+• Some knowledge and coursework related to Large Language Models, generative AI applications, and/or agentic AI concepts
+• A foundational understanding of programming concepts, ideally with some exposure to languages like Python or C++
+• A proactive attitude and eagerness to learn about emerging AI methodologies and tools
+• A genuine passion for staying informed about the latest advancements in the field of Artificial Intelligence
+• Basic familiarity with operating systems and common networking protocols is a plus
+• A willingness to embrace a growth mindset and contribute to end-to-end product thinking",2026,Bachelors,0,"Python, LLMs, GenAI, ML, Agents","Communication, Problem Solving"
+51,AI Developer,Internship,"• Basic knowledge of Python programming.
+• Understanding of Artificial Intelligence / Machine Learning concepts.
+• Familiarity with Generative AI, ChatGPT, OpenAI API, NLP, or LLMs is a plus.
+• Basic knowledge of TensorFlow, PyTorch, Scikit-learn, Pandas, or NumPy is an advantage.
+• Understanding of APIs and databases is preferred.
+• Strong analytical and problem-solving skills.
+• Passion for learning new AI technologies.
+• Final Year Students / Freshers / Recent Graduates.
+• B.E / B.Tech / BCA / MCA / B.Sc / M.Sc (Computer Science, AI, Data Science, IT, or related fields).
+• Candidates with mini-projects or AI-related knowledge are preferred. ",2026,Bachelors,0,"Python, ML, GenAI, LLMs, NLP, APIs, TensorFlow/PyTorch, Scikit-learn, Pandas, NumPy, SQL","Communication, Problem Solving"
+102,AI Engineer,Internship,"We are looking for candidates with strong programming skills, preferably in Python, hands-on experience with LLMs or AI systems, and a strong interest in agents, evaluation, alignment, interpretability, or enterprise AI.
+You should be comfortable working on ambiguous problems, building prototypes quickly, reading papers or technical material, documenting findings clearly, and independently identifying high-value directions.
+Bonus signals include experience with agent frameworks, long-horizon agents, evaluation pipelines, research projects, open-source tools, backend systems, enterprise data, or AI safety and interpretability. ",2026,Bachelors,0,"Python, ML, Agents, LangChain, LangGraph, LlamaIndex, LLMs","Communication, Problem Solving"
+116,AI Engineer,Internship,"• Currently pursuing or recently completed a degree in Computer Science, Engineering, Human-Computer Interaction (HCI), Data Science, or a related field.
+• Programming experience in Java and/or Python.
+• Understanding of software engineering fundamentals (data structures, APIs, modular design).
+• Basic familiarity with UX principles such as usability, accessibility, and user-centered design.
+• Strong interest in AI, machine learning, or Generative AI technologies. ",2026,Bachelors,0,"Python, Java, Full Stack, ML, GenAI, APIs","Communication, Problem Solving"
+120,AI Developer,Internship,"Bachelor's Degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field
+Fresh graduates are encouraged to apply
+Candidates who have completed AI/ML courses, certifications, bootcamps, or training programs can also apply
+Internship experience in AI, ML, Data Science, or related domains will be an added advantage
+Basic knowledge of Machine Learning concepts and algorithms
+Familiarity with Python programming
+Understanding of AI frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, or similar tools
+Basic understanding of data structures, databases, and APIs
+Strong analytical and problem-solving skills
+Passion for learning and exploring emerging AI technologies",2026,Bachelors,0,"Python, TensorFlow/PyTorch, Scikit-Learn, APIs, SQL","Communication, Problem Solving"
+122,AI Engineer,Internship,"• Collaborate with senior engineers to design and implement AI algorithms.
+• Assist in testing and debugging AI models to ensure accuracy and efficiency.
+• Research and experiment with new AI technologies to enhance product performance.
+• Participate in team meetings and brainstorming sessions to contribute ideas and insights.
+• Analyze data sets and generate reports to support decision-making processes.
+• Help in optimizing and fine-tuning AI models to improve overall system performance.
+• Stay updated on the latest trends and advancements in the AI industry to enhance your skills and knowledge. 
+127,AI Engineer,Internship,"• Foundational knowledge of programming concepts (e.g., Python or similar languages) and familiarity with data structures.
+• Basic understanding of artificial intelligence and machine learning principles, such as supervised learning, classification, or recommendation systems.
+• Ability to work with datasets, including data collection, cleaning, and simple analysis using tools like spreadsheets or basic libraries.
+• Strong analytical and problem-solving skills, with attention to detail and an interest in education technology.
+• Effective written and verbal communication skills, with the ability to collaborate in a remote, cross-functional team environment.
+• Current enrollment in or recent completion of a degree program in Computer Science, Data Science, Engineering, Mathematics, or a related field is preferred.
+• Interest in K–12 education, student development, and building inclusive, learner-focused technology solutions.
+• Self-motivated, organized, and able to manage tasks independently in a remote setting. ",2026,Bachelors,0,"Python, ML, Pandas, NumPy, LLMs","Communication, Problem Solving"
+132,AI Engineer,Internship,"• Collaborate with senior engineers to design and implement AI algorithms.
+• Assist in testing and debugging AI models to ensure accuracy and efficiency.
+• Research and experiment with new AI technologies to enhance product performance.
+• Participate in team meetings and brainstorming sessions to contribute ideas and insights.
+• Analyze data sets and generate reports to support decision-making processes.
+• Help in optimizing and fine-tuning AI models to improve overall system performance.
+• Stay updated on the latest trends and advancements in the AI industry to enhance your skills and knowledge. 
+134,AI Engineer,Internship,"1. Collaborate with senior engineers to design and implement AI algorithms.
+2. Assist in testing and debugging AI models to ensure accuracy and efficiency.
+3. Research and experiment with new AI technologies to enhance product performance.
+4. Participate in team meetings and brainstorming sessions to contribute ideas and insights.
+5. Analyze data sets and generate reports to support decision-making processes.
+6. Help in optimizing and fine-tuning AI models to improve overall system performance.
+7. Stay updated on the latest trends and advancements in the AI industry to enhance your skills and knowledge.
+If you are a self-motivated individual with a strong foundation in Python and a keen interest in AI technology, this internship opportunity at The Inventar company is perfect for you. Join us in shaping the future of AI technology and make a real impact on the world. Apply now and be part of our dynamic team! ",2026,Bachelors,0,"Python, LLMs, GenAI, ML","Communication, Problem Solving"
+136,AI Engineer,Internship,"- Foundational knowledge of AI/ML concepts such as supervised and unsupervised learning, model evaluation, and basic statistics.
+- Proficiency in at least one programming language commonly used in AI (e.g., Python) and familiarity with version control tools (e.g., Git).
+- Exposure to machine learning or deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn), even at a project or coursework level.
+- Ability to work with data: basic data cleaning, preprocessing, and visualization skills using tools such as NumPy, pandas, or similar libraries.
+- Strong analytical and problem-solving skills, with the ability to learn new tools and techniques quickly in a research-oriented environment.
+- Transparent written and verbal communication skills and the ability to collaborate effectively in a remote, distributed team.
+- Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (or equivalent practical experience).
+- Interest in XR, AI applications for interactive environments, and emerging technologies; prior personal or academic projects in these areas are a plus.
+- Familiarity with basic software development practices, including debugging, testing, and documenting code.
+- Self-motivated, organized, and able to manage time effectively in a fully remote internship setting. ",2026,Bachelors,0,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, Git, Github, Pandas, NumPy, MLOps","Communication, Problem Solving"
+137,AI Engineer,Internship,"Selected Intern's Day-to-day Responsibilities Include
+• Contribute to the development and implementation of AI algorithms and models.
+• Collaborate with our team to optimize and enhance existing AI technologies.
+• Conduct research and analysis to identify opportunities for AI integration.
+• Assist in data collection, cleansing, and preprocessing for AI projects.
+• Participate in testing and evaluation of AI solutions to ensure functionality and accuracy.
+• Stay up-to-date with the latest advancements in AI and machine learning.
+• Present findings and recommendations to stakeholders, contributing to the overall success of our AI initiatives. 
+138,AI Engineer,Internship,"• Design and develop innovative AI models and algorithms to solve complex problems.
+• Collaborate with cross-functional teams to integrate AI solutions into existing systems.
+• Develop and maintain large-scale data pipelines and architectures.
+• Conduct thorough analysis and testing of AI models to ensure quality and reliability.
+• Stay updated with industry trends and advancements in AI and machine learning.
+• Participate in code reviews and contribute to improving overall code quality. 
+139,AI Developer,Internship,"• Good knowledge of React.js and frontend development
+• Basic backend knowledge with Node.js
+• Understanding of JavaScript, HTML, and CSS
+• Basic understanding of REST APIs and Git
+• Interest or knowledge in AI, chatbots, LLMs, OpenAI APIs, prompt engineering, or NLP
+• Strong analytical and problem-solving skills
+• Clear communication skills for team collaboration and documentation
+• Interest in full-stack development and AI-based product building
+Good to Have
+• Python knowledge
+• Experience with chatbot projects
+• Experience with AI/ML or automation tools
+• Any GitHub or project portfolio
+• Understanding of no-code/low-code platforms
+• Familiarity with databases, cloud platforms, or AI frameworks ",2026,Bachelors,0,"Python, ML, Javascript, React, Git, Github, APIs, LLMs, OpenAI, Prompt Enginerring, NLP","Communication, Problem Solving"
+140,AI Developer,Internship,"• Python, FastAPI
+• Frontend basics (React/Next.js or similar) — enough to prototype and ship
+• Deployment (Docker, basic cloud infra)
+AI & LLM Stack:
+• LLMs, embeddings, vector databases (Pinecone, Weaviate, Qdrant, etc.)
+• RAG architectures — chunking, retrieval, reranking
+• AI agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, etc.)
+• Voice AI (Whisper, Deepgram, ElevenLabs, or similar TTS/STT models)
+• AI automation and orchestration (n8n, Zapier AI, custom agents)
+Tooling:
+• Cursor, Claude Code, GitHub Copilot — as daily drivers, not occasional toys
+• Web scraping (BeautifulSoup, Playwright, Scrapy, or API-based extraction)
+• Social data pipelines (Twitter/X, LinkedIn, Reddit, etc.) ",2026,Bachelors,0,"Python, ML, APIs, React, Javascript, Docker, LLMs, RAG, VectorDB, LangChain, LangGraph, CrewAI, AutoGen, n8n, GenAI","Communication, Problem Solving"
+141,AI Developer,Internship,"• Python and/or Java (strong focus on backend logic)
+• SQL (PostgreSQL preferred)
+• Basic understanding of NoSQL (MongoDB concepts)
+• REST APIs & JSON
+AI & Automation Tools
+• Claude Code / OpenAI APIs (or similar LLM tools)
+• AI-assisted development workflows
+• Automation tools & scripting
+System Concepts
+• Client-server architecture
+• Basic system design thinking
+• API integrations
+• Data flow understanding
+Preferred Skills
+• Strong logical thinking and problem-solving ability
+• Interest in AI tools and automation systems
+• Ability to build small tools quickly (scripts, utilities, internal apps)
+• Understanding of Git/GitHub basics
+• Curiosity to learn backend systems deeply
+• Comfort working across multiple backend technologies ",2026,Bachelors,0,"Python, ML, SQL, Java, APIs,LLMs, APIs, OpenAI, Git, Github","Communication, Problem Solving"
+145,AI Developer,Internship,"Interns will get hands-on exposure to frontend and backend development, API integration, ERP/business applications, and AI-assisted development workflows. Candidates with knowledge of Python, React.js, Angular, and modern AI tools such as ChatGPT, GitHub Copilot, Claude, or Gemini will have an added advantage.
+This internship is ideal for freshers and students who want to strengthen their technical skills, improve problem-solving abilities, and work closely with experienced developers on practical projects.
+Responsibilities include
+• Assisting in web and application development
+• Working with APIs and databases
+• Supporting frontend and backend development tasks
+• Debugging and testing applications
+• Learning and contributing to real-time projects ",2026,Bachelors,0,"Python, SQL, React, Javascript, GenAI","Communication, Problem Solving"
+146,AI Developer,Internship,"• Must-Have: Python or JavaScript (strong basics), API understanding, Basic LLM knowledge: Tokens, Context Prompting, Critical (Filter Here), Can build, not just explore, Understands: MCP / tool calling, How LLM apps actually work, Cursor, Antigravity
+• Good to Have: RAG / vector DB, FastAPI / Node backend, GitHub projects
+Ideal Candidate:
+• Builds side projects
+• Actively explores new AI tools
+• Thinks: “How can I use this in real product?”
+• Not a YouTube learner, a doer ",2026,Bachelors,0,"Python, APIs, Javascript, LLMs, RAG, VectorDB, Github, Git, MCP","Communication, Problem Solving"
+147,AI Developer,Internship,"• 1. Automation and workflow design with strong logical reasoning and test automation skills.
+• 2. Experience with Power Automate.
+• 3. Working knowledge of n8n, Make.com, Zapier, and similar automation platforms.
+• 4. Experience building and managing AI agents and LLMs.
+• 5. Understanding of LLM evaluation and response quality optimization.
+• 6. Proficiency in Python for automation and integrations.
+• 7. Strong understanding of APIs, JSON, and webhooks.
+• 8. Basic knowledge of web development fundamentals.
+• 9. Proficiency in Adobe Illustrator, Photoshop, and Canva.
+• 10. Ability to create photorealistic mockups with accurate lighting, textures, and perspective.
+• 11. Understanding of motion design basics using tools like After Effects.
+• 12. Experience with AI image generation tools
+• 13. Experience with AI video generation tools 
+148,AI Developer,Internship,"• Pursuing or recently completed a Bachelor's or Master's degree in:
+• Computer Science
+• Artificial Intelligence
+• Data Science
+• Information Technology
+• Related Engineering discipline
+• Strong programming skills in Python
+• Understanding of data structures, algorithms, and software engineering fundamentals
+• Basic knowledge of:
+• Machine Learning
+• Generative AI
+• APIs and Web Services
+• Databases
+• Git
+Preferred Skills
+• Experience with:
+• OpenAI APIs
+• LangChain
+• LlamaIndex
+• CrewAI
+• AutoGen
+• Vector databases
+• FastAPI
+• Docker
+• Azure or AWS
+• Personal AI projects, GitHub contributions, or hackathon participation 
+150,AI Developer,Internship,"• Programming: Strong proficiency in Python.
+• AI Frameworks: Solid understanding of LangChain and experience working with LLMs (e.g., OpenAI API, Anthropic, or local models).
+• Development Environment: Deep comfort with VS Code and Git/GitHub version control.
+• Core Skills: Ability to design logical workflows and handle API-based integrations.
+• Education: Pursuing or completed B.Tech/BCA/B.Sc in Computer Science or related fields.",2026,Bachelors,0,"Python, ML, Agents, LangChain, LangGraph, Git, Github, APIs, LLMs, OpenAI","Communication, Problem Solving"
+151,AI Developer,Internship,"Required Skills & QualificationsRecently completed a degree in Computer Science, AI, ML, Data Science, or related fieldsStrong understanding of Generative AI and LLM fundamentalsProficiency in PythonExperience or familiarity with:RAG architecturesPrompt engineeringVector databases (FAISS, Pinecone, Chroma, etc.)Good problem-solving and analytical skillsAbility to work independently in a remote environmentTools & Technologies (Exposure to Any Is a Plus)LangGraph for agent workflowsStrands or similar agent frameworksA2A (Agent-to-Agent) protocolsLLM frameworks such as LangChainOpenAI / open-source LLMsREST APIs and JSON-based integrationsGood to HaveExperience building AI agents or copilotsKnowledge of NLP, embeddings, and semantic searchFamiliarity with cloud platforms or deployment workflowsPrior hands-on projects in Generative AI or agent-based systemsWhat Youll GainReal-world experience building Generative AI & agentic systems ",2026,Bachelors,0,"Python, ML, GenAI, RAG, Prompt Engineering, VectorDB, LLMs, LangChain, LangGraph, Agents, OpenAI, NLP","Communication, Problem Solving"
+152,AI Developer,Internship,"• Basic understanding of Machine Learning / Deep Learning concepts
+• Familiarity with Python and AI libraries (NumPy, Pandas, TensorFlow, PyTorch)
+• Interest in working with LLMs, NLP, and AI automation
+• Experience with small AI/ML projects (college, personal, course-based) is a plus
+• Knowledge of data preprocessing and model evaluation methods
+• Willingness to learn fast and try out new AI tools and techniques
+• Good research skills and curiosity about modern AI advancements
+• Ability to commit 20 hours per week ",2026,Bachelors,0,"Python, ML, NLP, LLMs, NumPy, Pandas, TensorFlow/PyTorch, Scikit-Learn","Communication, Problem Solving"
+153,AI Developer,Internship,"• Develop and improve frontend pages, dashboards, forms, tables, filters, and user interfaces for company operations.
+• Work on backend APIs, database models, authentication, role-based access, and business workflow logic.
+• Integrate AI/LLM features for report generation, data search, assistant workflows, automated summaries, and operational automation.
+• Build automation flows for tasks, reminders, notifications, customer follow-ups, production updates, and internal coordination.
+• Integrate third-party APIs such as email, WhatsApp, cloud storage, CRM, ERP or accounting tools, and other business systems.
+• Support deployment, debugging, monitoring, and maintenance of web applications on cloud platforms.
+• Work with databases, file storage, dashboards, and real-time business data.
+• Identify bugs, improve performance, and support testing of new features before release.
+• Prepare basic technical documentation for features, APIs, workflows, and deployment steps.
+• Coordinate with internal teams to understand operational requirements and convert them into software features. 
+154,AI Developer,Internship,"• Exposure to LangChain, RAG, Vector Databases, AI Chatbots, or related projects.
+• Knowledge of AWS, Azure, or Google Cloud is a plus. ",2026,Bachelors,0,"Python, Agents, RAG, LangChain, LangGraph, VectorDB, AWS/Azure","Communication, Problem Solving"
+155,AI Developer,Internship,"Required Skills
+. Programming Languages
+· Python
+· JavaScript
+· JSON
+· HTML
+· Markdown
+AI & Automation Technologies
+· N8N
+· Ollama
+· Claude Code
+· CrewAI
+· AutoGen
+· FastAPI
+· Google AI Studio
+· MCP CLI
+LLM & Generative AI Frameworks
+· LangChain
+· LangFlow
+· Langfuse
+· Prompt Engineering
+· Language Interface Engineering
+· RAG (Retrieval-Augmented Generation)
+· Knowledge Graphs
+AI Infrastructure & Tools
+· Stability Matrix
+· Model Integration & Deployment
+· API Development & Integration
+Preferred Qualifications
+· Bachelor's Degree in Computer Science, Information Technology, AI/ML, or related field.
+· Strong understanding of Generative AI concepts.
+· Basic knowledge of Large Language Models (LLMs).
+· Familiarity with AI automation platforms and agentic AI systems.
+· Good problem-solving and analytical skills.
+· Strong communication and teamwork abilities.",2026,Bachelors,0,"Python, Javascript, n8n, CrewAI, AutoGen, APIs, MCP, Agents, LangChain, LangGraph, Prompt Engineering, RAG, LLMs","Commuication, Problem Solving"
+156,AI Developer,Internship,"as an AI & ML / Full Stack Developer Intern. Work on AI models, web applications, APIs, databases, and real-world projects. 2-month unpaid internship with hands-on training.  ",2026,Bachelors,0,"Python, ML, APIs, SQL","Communication, Problem Solving"
+157,AI Developer,Internship,"1. Collaborate with the development team to design, develop, and implement new features for AI applications.
+2. Develop backend functionalities using Python
+3. Deploy and manage applications on AWS for optimal performance and reliability.
+5. Conduct thorough testing and debugging to ensure high-quality code and functionality.
+6. Stay updated on industry trends and best practices to contribute innovative ideas to the team. ",2026,Bachelors,0,"Python, ML, AWS/Azure","Communication, Problem Solving"
+158,AI Developer,Internship,"• Basic knowledge of web development
+• Understanding of HTML, CSS, JavaScript
+• Familiarity with React, Node.js, or Python is a plus
+• Interest in AI and emerging technologies
+• Strong problem-solving skills
+• Ability to learn quickly and work independently 
+The intern will gain hands-on experience with:
+• Claude
+• Codex
+• Google Antigravity
+• Modern AI coding and automation tools
+• React / Next.js
+• Node.js
+• Python
+• REST APIs
+• Git & GitHub",2026,Bachelors,0,"Python, Javascript, React, Git, Github, GenAI, APIs","Communication, Problem Solving"
+159,AI Developer,Internship,"• LLMs & OpenAI:
+• Hands-on experience with OpenAI GPT (3.5, 4, 4-turbo) APIs
+• Experience building custom GPTs or AI assistants
+• Understanding of function calling, tool use, prompt design, and system messages
+• Prompt Engineering & Model Programming:
+• Crafting efficient and task-specific prompts
+• Fine-tuning and optimizing LLMs or integrating with vector databases like Pinecone or FAISS
+• Good understanding of RAG pipelines, embeddings, and LLMOps practices
+Nice to Have:
+• Experience in LangChain, LlamaIndex, or similar frameworks
+• Familiarity with deploying models on cloud platforms (AWS, GCP, Azure)
+• Prior work in building chatbots, agents, or AI-driven automation tools ",2026,Bachelors,0,"Python, LLMs, OpenAI, APIs, Prompt Engineering, VectorDB, RAG, MLOps, Agents, LangChain, LangGraph, LlamaIndex, AWS/Azure","Communication, Problem Solving"
+160,AI Developer,Internship,"Required Skills
+• Strong knowledge of Python.
+• Experience with Machine Learning and Deep Learning frameworks.
+• Knowledge of Generative AI, LLMs, and Prompt Engineering.
+• Familiarity with TensorFlow, PyTorch, Scikit-learn, or similar tools.
+• Understanding of APIs and AI model integration.
+• Knowledge of data preprocessing and model evaluation techniques.
+• Good problem-solving and analytical skills.
+Preferred Skills
+• Experience with OpenAI, LangChain, RAG, Vector Databases, or AI Agents.
+• Knowledge of cloud platforms (AWS, Azure, or GCP).
+• Experience in chatbot or automation projects.
+Qualification
+• Bachelor's degree in Computer Science, IT, AI, or a related field.
+• Relevant certifications in AI/ML are a plus. ",2026,Bachelors,0,"Python, ML, GenAI, TensorFlow/PyTorch, Scikit-Learn, Prompt Engineering, APIs, Agents, LangChain, RAG, OpenAI, VectorDB, AWS/Azure","Communication, Problem Solving"
+161,AI Developer,Internship,"Develop and implement AI/ML models for real-world applications.
+Work on Generative AI solutions using LLMs such as GPT, Claude, and Gemini.
+Build AI-powered chatbots, voice assistants, and automation tools.
+Perform data collection, cleaning, preprocessing, and analysis.
+Integrate AI APIs and models into web and mobile applications.
+Fine-tune and evaluate machine learning models.
+Research emerging AI technologies and recommend improvements.
+Document AI solutions, workflows, and technical specifications 
+162,AI Developer,Internship,"• 1. Basic understanding of Artificial Intelligence and Large Language Models (LLMs).
+• 2. Knowledge of Python programming is preferred.
+• 3. Familiarity with APIs and system integrations.
+• 4. Experience with automation tools such as n8n, Zapier, Make, or similar platforms.
+• 5. Understanding of prompt engineering concepts and techniques.
+• 6. Knowledge of databases is an added advantage.
+• 7. Strong analytical thinking and reasoning abilities.
+• 8. Problem-solving mindset with attention to detail.
+• 9. Ability to understand and evaluate business processes.
+• 10. Good written and verbal communication skills.
+• 11. Curiosity and enthusiasm for exploring emerging AI technologies. 
+163,AI Developer,Internship,"Required Skills & Qualifications:-
+• Strong foundation in Python programming.
+• Basic understanding of AI/ML concepts and their practical applications.
+• Basic Knowledge of GenAI.
+• Familiarity with handling datasets and preprocessing techniques.
+• Good logical, analytical, and problem-solving skills.
+• Knowledge or Hands-on experience with Django will be preferred.
+• Excellent academic record: 80%+ in 10th, 12th, and Graduation.
+• Pursuing or recently completed Bachelor’s/Master’s in Computer Science, Data Science, AI/ML, or related field. ",2026,Bachelors,0,"Python, ML, GenAI, Django","Communication, Problem Solving"
+164,AI Developer,Internship,"Skills required:
+SQL, PostgreSQL, JSON, Artificial intelligence, APIs, OpenAI API, Artificial Intelligence Markup Language (AIML) and Claude
+Other Requirements:
+• 1. Familier with n8n AI Workflow Automation
+• 2. Hands-on knowledge of n8n workflow automation.
+• 3. Knowledge of LLMs, AI APIs, and prompt-based automation.
+• 4. Familiarity with AI APIs ",2026,Bachelors,0,"Python, SQL, APIs, n8n, ML, LLMs","Communication, Problem Solving"
+165,AI Developer,Internship,"• Comfort using MERN Stack, Python languages and relational databases like PostgreSQL, my SQL, etc
+• Strong cloud computing experience with AWS etc.
+• 1-3 years of full stack software development experience ",2026,Bachelors,0,"Python, SQL, AWS/Azure","Communication, Problem Solving"
+166,AI Developer,Internship,"Skills required:
+MySQL, HTML, CSS, JavaScript, Python, Bootstrap, MongoDB, Node.js, GitHub, Express.js, React, REST API, TypeScript and Next.js ",2026,Bachelors,0,"Python, Javascript, Git, Github, React, SQL","Communication, Problem Solving"
+177,AI Developer,Internship,"Cloud Computing, Python, SQL, Machine Learning, Problem Solving, Natural Language Processing (NLP), PyTorch, Feature Engineering and Prompt Engineering",2026,Bachelors,0,"Python, SQL, ML, TensorFlow/PyTorch, NLP, Prompt Engineering","Communication, Problem Solving"
+178,AI Developer,Internship,"Required Skills Technical Skills
+• Strong knowledge of Python programming.
+• Familiarity with Machine Learning concepts and AI technologies.
+• Hands-on exposure to:
+• Scikit-learn
+• XGBoost
+• NumPy
+• PyTorch
+• TensorFlow
+• FastAPI
+• PostgreSQL
+Frontend / Development Skills
+• Node.js
+• React Native
+• Angular
+• Java
+• JavaScript
+Preferred Qualifications
+• Exposure to Generative AI tools and applications.
+• Good problem-solving and analytical skills.
+• Passion for technology and continuous learning.
+• Ability to work independently and in a team environment.",2026,Bachelors,0,"Python, SQL, ML, Scikit-Learn, NumPy, TemsorFlow/PyTorch, APIs, React, Javascript, Java, GenAI","Communication, Problem Solving"
+179,AI Developer,Internship,"What We Expect From You
+• Be able to learn fast on the job
+Absolute Requirement (Non-Negotiable)
+• A deployed web app
+• A GitHub repo with meaningful commits
+• A working AI tool
+• A live demo link
+• A product you built and shipped
+• An agent, automation, bot, or workflow you created
+These are not required but will strongly differentiate you:
+• Built projects using:
+• LLM APIs (OpenAI, Anthropic, etc.)
+• LangChain / LlamaIndex / custom agent frameworks
+• Vector DBs like Pinecone, Weaviate, FAISS
+• RAG systems
+• Experience deploying:
+• Vercel, Fly.io, Render, AWS, etc.
+• Built internal tools for a team before
+• Strong product intuition (you care about UX, not just code)
+• Experience automating your own workflows using scripts or AI 
+180,AI Developer,Internship,"What we are looking for
+Recent grad or final year student preferably at IIT/NIT
+Strong foundations: Proficiency in Python, coursework or projects in ML, NLP, or applied statistics
+Builder mindset: You are comfortable working with real world messy, large data sets. You can communicate your findings to non-technical stakeholders in plain language
+Nice to have: Prior exposure to B2B, SaaS, or enterprise software contexts — even through internships or projects. Experience with LLM APIs, prompt engineering, or RAG architectures ",2026,Bachelors,0,"Python, ML, NLP, Prompt Engineering, LLMs, APIs, RAG","Communication, Problem Solving"
+181,AI Developer,Internship,"What we're looking for
+• Hands-on experience (personal projects count!) with Cursor, Antigravity, or similar AI coding tools
+• Comfort with vibe coding — shipping first, perfecting second
+• Basic understanding of HTML, CSS, JavaScript, or any modern framework (React, Next.js, etc.)
+• Strong problem-solving mindset and ability to work independently
+• A portfolio, GitHub, or any proof of work you've built using AI tools
+Nice to have
+• Experience with AI agents, LLM APIs (OpenAI, Anthropic, etc.), or no-code/low-code tools
+• Familiarity with deployment platforms like Vercel, Netlify, or Railway
+• An eye for design — clean UIs are a bonus ",2026,Bachelors,0,"Python, Javascript, Github, Git, LLMs, APIs, OpenAI, React","Communication, Problem Solving"
+185,AI Developer,Internship,"Hands-on experience with Generative AI and LLMs
+Proven ability to deploy and run open-source models locally
+Practical experience with automation tools like n8n
+Strong foundation in Reinforcement Learning, CNNs, and Transformers
+Proficiency in Python, PyTorch/TensorFlow, and Hugging Face ecosystem
+Portfolio demonstrating AI/ML projects (GitHub repos, project demos)
+Self-starter with problem-solving mindset and passion for innovation
+Excellent communication and collaboration skills",2026,Bachelors,0,"Python, GenAI, LLMs, n8n, ML, TensorFlow/PyTorch, Hugging Face, Github, Git","Communication, Problem Solving"
+186,AI Developer,Internship,"Skills Required
+Candidates should have basic Python knowledge, interest in AI/ML, logical thinking, problem-solving skills, basic understanding of data, a positive attitude, and willingness to learn. Freshers can also apply",2026,Bachelors,0,"Python, ML, LLMs","Communication, Problem Solving"
+194,AI Developer,Internship,"Assist in designing, developing, and testing AI/ML models and applications.
+Work on Generative AI, NLP, Chatbots, and automation solutions.
+Support data collection, preprocessing, and analysis activities.
+Collaborate with developers and product teams on AI integrations.
+Research and experiment with the latest AI technologies and frameworks.
+Develop APIs and backend services for AI applications.
+Create technical documentation and project reports.
+Participate in code reviews and debugging sessions.
+195,AI Developer,Internship,"Strong experience in AI/ML model development and deployment
+Hands-on experience with NLP, computer vision, or generative AI projects
+Proven background in Python, TensorFlow, PyTorch, or similar frameworks
+Bonus: Prior experience developing CPaaS platforms or communication-based web applications
+Solid understanding of REST APIs, integrations, and cloud environments
+Excellent problem-solving and communication skills
+Ability to thrive in a fast-paced, agile startup ecosystem",2026,Bachelors,0,"Python, ML, NLP, GenAI, TensorFlow/PyTorch, APIs","Communication, Problem Solving"
+196,AI Developer,Internship,"Develop and implement AI models using Python and other relevant technologies.
+Collaborate with cross-functional teams to design and develop new features.
+Work on PDF/OCR extraction, accounting, and JavaScript tasks.
+Analyze data and create visualizations using JSON and SQL.
+Participate in code reviews and contribute to improving the overall quality of the codebase.
+Stay updated with industry trends and emerging technologies in AI and Pytho",2026,Bachelors,0,"Python, Javascript, SQL, ML","Communication, Problem Solving"
+197,AI Developer,Internship,"Strong knowledge of Python (preferably with frameworks like Flask, FastAPI).
+Familiarity with AI concepts such as Machine Learning, Deep Learning, Natural Language Processing (NLP), etc.
+Knowledge of AI libraries such as TensorFlow, Keras, PyTorch, or Scikit-Learn.
+Experience with SQL or NoSQL databases (e.g., MySQL, MongoDB).
+Basic understanding of RESTful APIs and data serialization formats like JSON and XML.
+Familiarity with version control systems like Git.
+Understanding of OOP (Object-Oriented Programming) concepts.
+Ability to work with cloud platforms (AWS, Google Cloud, etc.) is a plus.",2026,Bachelors,0,"Python, APIs, ML, TensorFlow/PyTorch, Scikit-Learn, NLP, SQL, Git, Github, AWS/Azure","Communication, Problem Solving"
+192,AI Developer,Internship,"Assist in designing, developing, and testing AI/ML models and applications.
+Work on Generative AI, NLP, Chatbots, and automation solutions.
+Support data collection, preprocessing, and analysis activities.
+Collaborate with developers and product teams on AI integrations.
+Research and experiment with the latest AI technologies and frameworks.
+Develop APIs and backend services for AI applications.
+Create technical documentation and project reports.
+Participate in code reviews and debugging sessions.",2026,Bachelors,0,"Python, ML, GenAI, NLP, APIs","Communication, Problem Solving"
+199,AI Developer,Internship,"Develop and implement AI models using Python and other relevant technologies.
+Collaborate with cross-functional teams to design and develop new features.
+Work on PDF/OCR extraction, accounting, and JavaScript tasks.
+Analyze data and create visualizations using JSON and SQL.
+Participate in code reviews and contribute to improving the overall quality of the codebase.
+Stay updated with industry trends and emerging technologies in AI and Python",2026,Bachelors,0,"Python, Javascript, SQL, ML","Communication, Problem Solving"
+200,AI Developer,Internship,"Interest in Generative AI, Large Language Models (LLMs), and AI Agentic Systems is an advantage.
+Basic knowledge of programming languages such as C#, Python, or similar technologies.
+Understanding of Object-Oriented Programming (OOP) concepts.
+Familiarity with databases and SQL queries.
+Basic understanding of web technologies (HTML, CSS, JavaScript).
+Strong analytical, problem-solving, and communication skills.
+Eagerness to learn new technologies and adapt to a fast-paced environment.
+Ability to work from the Hyderabad office throughout the internship period",2026,Bachelors,0,"Python, LLMs, C#, Agents, SQL, Javascript, GenAI","Communication, Problem Solving"
+201,AI Developer,Internship,"What You ll Do (Responsibilities)
+AI-Pair Programming: Use tools like antigravity, GitHub Copilot, Cursor, or Claude Dev to build production-ready features, focusing on architectural logic while the AI handles the syntax.
+Prompt Engineering for Code: Create and maintain a Prompt Library for the team to automate repetitive tasks like unit testing, documentation, and SQL migrations.
+Code Verification: Act as the Human-in-the-loop to audit AI-generated code for security flaws, technical debt, and logical errors.
+RAG & Tooling: Assist in building internal AI tools (using LangChain or LlamaIndex) that help our senior devs navigate our massive internal codebase.
+Performance Benchmarking: Help track Developer Velocity measuring how much faster we ship code with AI assistance vs. traditional methods.",2026,Bachelors,0,"Python, Github, Git, Prompt Engineering, SQL, Agents, LangChain, LangGraph, LlamaIndex, RAG, GenAI ","Communication, Problem Solving"

frontend/data/clean/cleaned_job_descriptions_junior.csv

@@ -0,0 +1,801 @@
+id,role,type,job_desc,year,qualification,experience,tech_skills,soft_skills
+5,AI Engineer,Junior,"AI/ML models, Python, Core ML concepts, ML framework (Scikit‑learn/TensorFlow/PyTorch), MLOps, SQL/NoSQL, Messaging/queue systems 
+0–1 year of experience as an AI/ML Engineer, Data Scientist, or similar role, or strong academic/personal projects in AI/ML.
+Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or equivalent practical experience.
+Solid Python skills for data processing and model development.
+Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, overfitting, etc.
+Experience with at least one ML framework (e.g., scikit‑learn, TensorFlow, or PyTorch).
+Ability to work with databases (SQL/NoSQL) and basic messaging/queue systems to move data in and out of models.
+Strong problem‑solving mindset, eagerness to learn, and comfort working in a fast‑moving environment.
+Good communication skills and willingness to collaborate in a team and with non‑technical stakeholders.",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, MLOps, Model Training, Feature Engineering","Communication, Problem Solving"
+6,AI Engineer,Junior,"4–5 years of proven development experience in AI/ML for embedded device
+Strong expertise in deep learning frameworks (TensorFlow, PyTorch, ONNX, TensorRT).
+Expert proficiency with open-source infrastructure tools like llama.cpp, vLLM, Ollama, and NVIDIA Triton Inference Server for local model serving, high-throughput inference, and quantization.
+Hands-on experience building complex, stateful workflows and tracking applications using LangChain, LangGraph, and Langfuse.
+Expertise in selecting, benchmarking, and adapting state-of-the-art open-source architectures (such as Llama 3, gemma, Qwen, and Kimi) for enterprise tasks
+Practical experience with edge/embedded AI (NVIDIA Jetson, Qualcomm, ARM).
+Proficiency in NLP / Conversational AI / Speech interfaces ( ASR, TTS )
+Solid programming skills in Python and C++/Java for optimization and integration.
+Solid understanding of application development in embedded Linux / Android
+Familiarity with automotive standards, protocols such as CAN
+Familiarity with cloud ML services like AWS SageMaker or Azure ML
+Good communication skills and great team spirit.
+Experience working with embedded Linux, Automotive Android
+Knowledge of vehicle data interfaces (CAN, OBD-II, sensors).
+Exposure to LLMOps & MLOps pipelines and cloud platforms (AWS/GCP/Azure).
+",2026,Bachelors,5-10,"Python, C++, Java, TensorFlow/PyTorch, vLLM, Ollama, LangChain, LangGraph, NLP, AWS/Azure, MLOps","Communication, Problem Solving"
+8,AI Engineer,Junior,"Proficiency in C/C++ and python programming
+Hands-on experience in deploying AI models on embedded platforms.
+Experience working with MCU, bare-metal, RTOS and Edge AI/ML applications
+Experience working with multi-core, multi-threaded applications, IPC and task scheduling
+Strong knowledge in board bring-up and interfaces such as OSPI, GPIO, UART, SRAM, SDRAM etc.
+Good debugging and problem-solving skills.
+Experience in various profiling tools, and proficiency in identifying deviations from expected behaviour and finding their root causes
+Ability to use Hardware test equipment: Joulescope, oscilloscope, logic analyzer and JTAG
+Understanding of system constraints like memory, compute, and power on edge devices.
+Good communication skills for clearly communicating ideas and concepts to team/customer",2026,Bachelors,0-1,"Python, C, C++, Sytem Design, Model Evaluation","Communication, Problem Solving"
+14,AI Engineer,Junior,"Basic understanding of AI, Machine Learning, or Automation concepts
+Familiarity with Python / APIs / No-code & Low-code tools (preferred but not mandatory
+Good problem-solving and logical thinking skills
+Willingness to learn and adapt quickly
+Good communication skills",2026,Bachelors,0-1,"Python, ML, APIs","Communication, Problem Solving"
+16,AI Engineer,Junior,"Docker / Containerization
+AWS / Azure / GCP exposure
+AI Agent workflow understanding
+ML fundamentals
+Enterprise AI integration experience",2026,Bachelors,0-1,"Python, ML, Docker, AWS/Azure, ","Communication, Problem Solving"
+17,AI Engineer,Junior,"1+ years of experience in AI, LLMs, automation, or related systems
+Strong Python programming skills with experience in APIs and backend integration
+Hands-on experience in prompt engineering, LLM orchestration, and evaluation
+Familiarity with LangChain, embeddings, vector databases, and RAG systems
+Strong problem-solving skills with ability to build and ship MVPs quickly
+Passion for AI, automation, and real-world product development
+Strong ownership mindset
+Ability to work in fast-paced startup environments
+Good understanding of AI product thinking and user experience
+Strong communication and collaboration skills
+",2026,Bachelors,1-5,"Python, APIs, LLMs, Prompt Engineering, LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen,  Anthropic /OpenAI SDKs, MCP, VectorDB, n8n, RAG, Agents","Communication, Problem Solving, Ownership"
+18,AI Developer,Junior,"Strong Python programming
+Experience with FastAPI, Flask, or similar backend frameworks
+Understanding of REST APIs
+Familiarity with cloud platforms (AWS) - Exposure to services like S3, EC2, Lambda, or API Gateway is a plus
+Experience working with AI/LLM APIs
+Knowledge of data processing (CSV, JSON, Pandas)
+Familiarity with Git and version control
+Basic understanding of Docker and cloud deployment
+Experience with RAG pipelines
+Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
+Experience parsing PDF documents
+Knowledge of LangChain or LlamaIndex
+Basic frontend knowledge (React / simple JS)
+",2026,Bachelors,0-1,"Python, React, Javascript, APIs, AWS/Azure, LLMs, Git, Docker, RAG, VectorDB, LangChain","Communication, Problem Solving"
+19,AI Engineer,Junior,"Degree in Computer Science, AI, or a related field (or equivalent practical experience).Strong command of Python, JavaScript, or other common programming languages.Hands-on experience with prompt engineering, LLMs, and AI-assisted coding tools.Familiarity with cloud-based IDEs, version control (e.g., Git), and API integrations.Excellent communication skills for client-facing interactions (live and written).Comfortable working independently in a remote, fast-paced environment.",2026,Bachelors,0-1,"Python, Javascript,  LLMs, Prompt Engineering, APIs","Communication, Problem Solving"
+22,AI Engineer,Junior,"Strong programming skills in Python.
+Experience with LLM architectures, prompt engineering, and RAG systems.
+Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
+Experience with vector databases like Pinecone, Weaviate, or Milvus.
+Azure expertise as must have, while AWS & GCP",2026,Bachelors,0-1,"Python, LLMs, Prompt Engineering, RAG, TensorFlow/PyTorch, VectorDB, AWS/Azure","Communication, Problem Solving"
+26,AI Engineer,Junior,"Strong hands-on experience in Python programming
+Ability to code independently without relying on AI coding tools
+Basic understanding of AI/ML concepts and frameworks
+Knowledge of APIs, data structures, and problem-solving techniques
+Good communication and collaboration skills
+Self-motivated with a strong learning attitude
+Familiarity with Generative AI, LLMs, or automation tools
+Understanding of libraries such as Pandas, NumPy, Scikit-learn, or FastAPI
+Exposure to Git/GitHub and cloud platforms is a plus
+Bachelor’s degree in Computer Science, IT, or related field
+Candidates with internship/project experience in AI/ML are encouraged to apply 
+",2026,Bachelors,0-1,"Python, APIs, GenAI, LLMs, Pandas, NumPy, Scikit-Learn, Git, Github","Communication, Problem Solving"
+35,AI Developer,Junior,"Strong foundation in Java, React, NodeJS, Python, SQL, and Excel Basic understanding of data structures, databases, and algorithms Exposure to pandas, NumPy, PySpark, scikit-learn, GenAI, Agentic AI or TensorFlow is a plus Familiarity with BI tools (e.g., Power BI, Tableau) or cloud platforms (e.g., AWS, GCP) is desirable Knowledge of version control (Git) is an advantage Soft Skills Curiosity and a passion for data-driven problem solving Strong analytical and logical thinking Good communication and collaboration skills Willingness to learn in a fast-paced environment Ability to break down complex problems and document clearly Preferred (Good to Have, Not Mandatory) Internship or academic project in data analytics, machine learning, or database systems Participation in hackathons, coding contests, or Kaggle competitions Exposure to Agile or collaborative tools like JIRA, Confluence ",2026,Bachelors,0-1,"Java, React, NodeJS, Python, SQL, Excel,  Pandas, NumPy, Scikit-Learn, GenAI, TensorFlow/PyTorch, Git, Github, AWS/Azure","Problem Solving, Strong analytical, logical thinking, Communication "
+36,AI Engineer,Junior,"Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
+Experience: 0 to 1 yr / 2025 Passouts / upcoming 2026 passouts Preferred Proficiency in Python programming with a strong grasp of core concepts.
+Basic Data Structures and Algorithms: Familiarity with common data structures (lists, dictionaries, tuples) and basic algorithms (sorting, searching) is advantageous.
+Problem-Solving Skills: Ability to analyse and solve programming problems using Python.
+Understanding of Object-Oriented Programming (OOP): Basic understanding of OOP principles like classes, objects, inheritance, and encapsulation
+Basic knowledge in Data Science including but not limited to ETL, EDA, Data Processing, Visualization etc.
+Familiarity with machine learning and deep learning models (e.g., TensorFlow, Keras, PyTorch).
+Experience working with SQL DMBS like PostgreSQL is a plus.
+Basic understanding of Natural Language Processing (NLP) concepts
+Knowledge of Python frameworks like Django
+Familiarity with Jira and Agile methodology will be an added advantage.
+Certification or experience in data analysis, data mining, and statistical modelling is an added advantage
+Strong knowledge of statistical concepts and techniques.
+Knowledge in data visualization tools (Tableau, Power BI, etc.) and SQL.
+Excellent problem-solving and analytical skills.
+Strong communication and presentation skills.
+Certification in Data Science is an added advantage. 
+",2026,Bachelors,0-1,"Python, TensorFlow/PyTorch,  SQL, NLP, PowerBI","Communication, Problem Solving"
+37,AI Engineer,Junior,"• 0–1 year of experience as an AI/ML Engineer, Data Scientist, or similar role, or strong academic/personal projects in AI/ML.
+• Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or equivalent practical experience.
+• Solid Python skills for data processing and model development.
+• Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, overfitting, etc.
+• Experience with at least one ML framework (e.g., scikit‑learn, TensorFlow, or PyTorch).
+• Ability to work with databases (SQL/NoSQL) and basic messaging/queue systems to move data in and out of models.
+• Strong problem‑solving mindset, eagerness to learn, and comfort working in a fast‑moving environment.
+• Good communication skills and willingness to collaborate in a team and with non‑technical stakeholders.
+• Experience running or fine‑tuning local LLMs (e.g., via Ollama) or other open‑source models.
+• Exposure to workflow automation, or operations-heavy domains.
+• Familiarity with basic MLOps tools (MLflow, DVC, Weights & Biases) and containerization (Docker).
+• Basic knowledge of any cloud platform (AWS, Azure, GCP) for deploying services.
+• Experience integrating ML models into web backends (REST APIs, microservices, Node.js/Next.js).
+• Understanding of vector databases or simple retrieval/RAG systems for LLM-based solutions.
+• Awareness of ethical AI, bias, and privacy considerations. 
+",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, MLOps, Model Training, Feature Engineering, RAG, AWS/Azure, LLMs","Communication, Problem Solving"
+43,AI Engineer,Junior,"• Strong programming skills in Python.
+• Understanding of Data Structures and Algorithms.
+• Knowledge of Machine Learning fundamentals.
+• Understanding of Natural Language Processing (NLP) concepts:
+• Tokenization
+• Embeddings
+• Text Classification
+• Named Entity Recognition (NER)
+• Semantic Search
+• Transformer Models
+• Understanding of Generative AI concepts:
+• Large Language Models (LLMs)
+• Prompt Engineering
+• RAG (Retrieval-Augmented Generation)
+• Fine-tuning concepts
+• AI Agent fundamentals
+• Familiarity with AI/ML frameworks:
+• PyTorch or TensorFlow
+• Hugging Face Transformers
+• LangChain, LlamaIndex, or similar frameworks
+• Understanding of model deployment and serving concepts.
+• Familiarity with:
+• Docker
+• Git/GitHub
+• CI/CD concepts
+• Kubernetes (basic understanding)
+• ML experiment tracking tools (MLflow, Weights & Biases, etc.)
+• Basic knowledge of SQL databases.
+• Familiarity with vector databases such as Pinecone, Weaviate, Qdrant, or ChromaDB.
+• Understanding of REST APIs and FastAPI.
+• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
+• Hands-on academic projects, internships, or personal projects in AI/ML.
+• Experience building chatbots, AI assistants, or NLP applications.
+• Contributions to open-source AI projects are a plus.
+• Familiarity with cloud platforms such as AWS, GCP, or Azure.
+• Strong problem-solving and analytical skills.
+• Passion for AI, Machine Learning, and emerging technologies.
+• Curiosity to learn and experiment with new AI frameworks and tools.
+• Good communication and teamwork skills.
+• Ability to work in a fast-paced, collaborative environment",2026,Bachelors,0-1,"Python, ML, NLP, MLOPS, Docker, GenAI, RAG, VectorDB, Agents, Prompt Engineering, TensorFlow/PyTorch, LangChain, LangGraph, Hugging Face, CI/CD, Git, Github, Kubernetes, MLflow, APIs, AWS/Azure","Communication, Problem Solving, Analytical Skills"
+55,AI Engineer,Junior,"• Strong understanding of RAG architecture — document chunking, embedding, retrieval, reranking, and synthesis.
+• Proficiency in Python, including libraries like Pandas,Numpy, and Scikit-learn.
+• Experience withFastAPIor Flask for microservice and API development.
+• Hands-on withLangGraph,LangChain, or MCP for multi-agent orchestration.
+• Familiarity with vector databases (FAISS,ChromaDB,Weaviate, Elasticsearch).
+• Good Working knowledge of ML/DL frameworks (TensorFlow,PyTorch).
+• Understanding of model serving via REST APIs, batch jobs, or pipelines.
+• Exposure to containerization (Docker) and scalable architecture patterns.
+• Familiarity with Git,MLflow, or DVC for versioning, tracking, and collaboration.
+• Awareness of cloud AI/ML services (Azure ML, AWS SageMaker, GCP Vertex AI).
+• Understanding of prompt evaluation, retrieval accuracy metrics, and contextual reasoning benchmarks.
+• Curiosity to explore Agentic AI frameworks and autonomous reasoning systems.
+• Analytical mindset with a focus on debugging, optimization, and scalability.
+• Strong communication and documentation skills for collaborative workflows.
+• Innovative and research-driven approach toward new AI architectures.
+• Eagerness to experiment, iterate, and learn from production-level systems. ",2026,Bachelors,0-1,"Python, ML, RAG, APIs, LangChain, LangGraph, MCP, TensorFlow/PyTorch, Docker, Git, Github, MLflow, AWS/Azure","Communication, Problem Solving"
+57,AI Engineer,Junior,"Bachelor's degree in a relevant field such as Computer Science, Data Science, or a related field
+1–2 years of professional experience building or supporting software or AI-driven systems in a work environment (internships and co-ops included)
+Hands-on experience working with LLM-based applications or agentic workflows in a professional or production setting
+Strong programming skills, including experience with: Python (preferred), Java (optional), Scala (optional)
+Experience working with APIs and backend development frameworks (e.g., Flask, FastAPI) in a job setting
+Familiarity with LLM frameworks or platforms (e.g., LangChain, LangGraph, OpenAI, Gemini)
+Basic SQL skills and experience working with structured and unstructured data
+Experience contributing to applications or pipelines deployed in cloud environments such as GCP, AWS, or Azure
+Understanding of data pipelines, APIs, and system integrations
+Excellent communication and collaboration skills in a team-based environment
+Ability to work independently and manage multiple tasks and priorities",2026,Bachelors,0-1,"Python, LLMs, Java, LangChain, LangGraph, OpenAI, SQL, AWS/Azure, ","Communication, Problem Solving"
+58,AI Engineer,Junior,"- Solid Python skills (async/await, type hints, standard library)
+- Experience building or consuming REST APIs (FastAPI, Flask, or Django)
+- Exposure to at least one LLM provider API
+- Comfort navigating and contributing to an existing codebase
+- Git workflow (branches, PRs)
+- MongoDB or PostgreSQL
+- Docker, AWS
+- pytest or any testing framework
+- Experience with LiteLLM, LangChain, or similar
+- AI coding tools (Cursor, Copilot, Claude)
+Interested Candidates can drop their cv at recruitment@qwikgig.com or can reach us out at 
+• LLM APIs: 1 year (Required)
+• Python: 1 year (Required)
+• Fast API: 1 year (Required)
+• Flask: 1 year (Required)
+• Django: 1 year (Required) ",2026,Bachelors,0-1,"Python, APIs, LLMs, Git, Github, VectorDB, SQL, Docker, AWS/Azure, LangChain, LangGraph, Django","Communication, Problem Solving"
+59,AI Engineer,Junior,"Python as primary language.
+Microsoft Azure required as the primary cloud platform.
+Hands-on experience building with Azure AI Foundry.
+Claude Code experience and expertise required, including hands-on development of skills and plugins on the platform. This is non-negotiable for the role.
+LangGraph experience required. Demonstrated ability to design state graphs, conditional edges, and multi-agent compositions.
+Model Context Protocol experience required. Comfortable designing tool calls and building protocol wrappers.
+Agentic pair programming with generative AI as the primary working mode. Prior experience is required.
+Pydantic for data validation and structured outputs across agent systems and APIs.
+SQL proficiency and PostgreSQL experience.
+Vector database experience (pgvector, Azure AI Search, or similar).
+Familiarity with modern data platforms such as Snowflake and Databricks.
+Multi-step agent systems with proper evaluation and validation.
+Strong fluency across modern frontier language models such as the GPT, Claude, and Gemini model families. Model selection is driven by the requirements of each task and the practical considerations of cost.
+The discipline to choose mature, proven frameworks for AI engineering work. Technical decisions are grounded in clear engineering justification and supported by data.
+Docker and containerization for development and deployment workflows.
+FastAPI or equivalent web frameworks for building APIs and backend services.
+Working knowledge of GitHub workflows, code review discipline, and infrastructure-as-code patterns.
+Although Microsoft Azure is the primary platform, Google Cloud Platform experience is also valuable and applicable to the practice's work.
+Familiarity with Azure Container Apps, Azure Kubernetes Services, or similar container orchestration platforms.
+Familiarity with Apache Software Foundation tools such as Apache Airflow, Apache Kafka, and Apache Flink.
+Experience with LangChain, PyTorch, or other AI and machine learning frameworks.
+CrewAI or other multi-agent frameworks.
+LlamaIndex for RAG and data ingestion workflows.
+Celery and Redis for background task processing and caching.
+Familiarity with A2A (Agent-to-Agent) protocol for inter-agent communication.
+Experience with modern natural language processing tools, including embedding models and entity recognition.
+Familiarity with vision-language model integration for multi-modal AI use cases.
+Experience working in regulated markets, including the compliance and risk-management disciplines such environments require.
+Playwright for end-to-end testing automation.
+Familiarity with hybrid architectures that integrate deterministic and generative AI techniques. ",2026,Bachelors,0-1,"Python, AWS/Azure, LangChain, LangGraph, APIs, MCP, SQL, VectorDB,n8n, LLMs, CrewAI, TensorFlow/Pytorch, Agents, RAG","Communication, Problem Solving"
+62,AI Engineer,Junior,"4 to 5 years of Python engineering or a CS degree with strong applied ML/NLP track record
+Hands-on with LLMs, prompt engineering, RAG architectures, and vector databases (Pinecone, Azure AI Search, or equivalent
+Experience with Azure OpenAI Service, LangChain, or similar orchestration frameworks
+Comfort working within a Microsoft Azure cloud environment
+Strong understanding of HIPAA/PIPEDA data handling — or fast learner in regulated environments
+Production mindset — you’ve shipped models, not just notebooks
+Healthcare SaaS or healthtech experience
+Experience with voice AI or conversational AI
+Familiarity with .NET8 or React integration patterns for AI services ",2026,Bachelors,0-1,"Python, Ml, NLP, LLMs, Prompt Engineering, RAG, VectorDB, LangChain, OpenAI, AWS/Azure, .NET, React","Communication, Problem Solving"
+63,AI Engineer,Junior,"• Strong foundation in Computer Science and Software Development, including algorithms, data structures, version control, and production-grade coding practices.
+• Hands-on experience with Neural Networks and Pattern Recognition, including training, tuning, and deploying deep learning models for classification, prediction, or recommendation tasks.
+• Practical expertise in Natural Language Processing (NLP), such as text classification, information extraction, embeddings, and working with modern NLP frameworks or large language models.
+• Proficiency with common AI/ML tools and frameworks (e.g., Python, PyTorch or TensorFlow, scikit-learn, Docker, cloud platforms such as AWS, GCP, or Azure).
+• Bachelor’s or higher degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience.
+• Experience building and deploying models into production environments, including working with APIs, microservices, and CI/CD pipelines.
+• Strong analytical and problem-solving skills, with the ability to translate business requirements into robust AI solutions.
+• Effective written and verbal communication skills, and the ability to collaborate with distributed, cross-functional teams across time zones.
+• Familiarity with MLOps practices, monitoring and observability for models, and responsible AI considerations (fairness, bias, and explainability) is a plus. ",2026,Bachelors,0-1,"Python, NLP, Python, TensorFlow/PyTorch, Scikit-Learn, Docker, AWS/Azure, API, CI/CD, MLOps","Communication, Problem Solving"
+65,AI Engineer,Junior,"• You have shipped multi-agent systems in production — not prototypes, not demos. Real users, real scale, real failure modes.
+• You have deep, hands-on experience with both vector databases and knowledge graphs, and critically, with combining them in hybrid retrieval architectures.
+• You understand orchestration frameworks (LangGraph, CrewAI, AutoGen, or equivalent) well enough to know when not to use one.
+• You can design retrieval pipelines that blend semantic search, graph traversal, and temporal signals — the kind of system that models like Ebbinghaus forgetting curves and Zeigarnik effects demand.
+• You have practical experience with protocol-level integration work connecting AI agents to external services and data sources.
+• You communicate architecturally — you can draw a system on a whiteboard and make a room of senior engineers and investors understand why it matters.
+• Background in cognitive science, computational neuroscience, or memory systems research — even informally.
+• Experience scaling AI systems in B2C (consumer-grade latency, UX sensitivity, personalization at scale).
+• Track record mentoring engineers and building AI-capable teams from strong traditional engineering foundations.
+• Contributions to open-source AI/ML infrastructure projects. ",2026,Bachelors,0-1,"Python, VectorDB, LangGraph, CrewAI, AutoGen, ML","Communication, Problem Solving"
+68,AI Engineer,Junior,"Bachelor's degree in a relevant field such as Computer Science, Data Science, or a related field
+1–2 years of professional experience building or supporting software or AI-driven systems in a work environment (internships and co-ops included)
+Hands-on experience working with LLM-based applications or agentic workflows in a professional or production setting
+Strong programming skills, including experience with: Python (preferred), Java (optional), Scala (optional)
+Experience working with APIs and backend development frameworks (e.g., Flask, FastAPI) in a job setting
+Familiarity with LLM frameworks or platforms (e.g., LangChain, LangGraph, OpenAI, Gemini)
+Basic SQL skills and experience working with structured and unstructured data
+Experience contributing to applications or pipelines deployed in cloud environments such as GCP, AWS, or Azure
+Understanding of data pipelines, APIs, and system integrations
+Excellent communication and collaboration skills in a team-based environment
+Ability to work independently and manage multiple tasks and priorities ",2026,Bachelors,0-1,"Python, LLMs, Agents, Python, Java, APIs, LangChain, LangGraph, OpenAI, SQL, AWS/Azure","Communication, Problem Solving"
+71,AI Engineer,Junior,"• Proficiency in Pattern Recognition and Neural Network design and implementation
+• Strong foundation in Computer Science with familiarity in algorithms, data structures, and computational models
+• Experience in Software Development, including coding, testing, debugging, and process optimization
+• Expertise in Natural Language Processing (NLP), including text analytics, language modeling, and contextual understanding
+• Hands-on experience with machine learning frameworks and AI tools is a plus
+• Comfortable working with distributed environments and large-scale data processing systems
+• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field
+• Excellent problem-solving skills, collaboration abilities, and a proactive mindset ",2026,Bachelors,0-1,"Python, ML, NLP","Communication, Problem Solving"
+75,AI Engineer,Junior,"• 3–6 years of experience in Data Science, Machine Learning, or AI Engineering.
+• Strong proficiency in Python for machine learning and data processing.
+• Hands-on experience in machine learning model development and deployment.
+• Experience working with Apache Kafka and streaming data processing.
+• Strong understanding of feature engineering, model evaluation, and production ML workflows.
+• Experience with AWS services including:
+• AWS Lambda
+• EventBridge
+• SageMaker
+• S3
+• Firehose
+• CloudWatch
+• Experience working with Snowflake and Snowpark.
+• Knowledge of SQL and large-scale data processing.
+• Experience building CI/CD pipelines and deployment automation.
+• Hands-on experience with Terraform and cloud infrastructure management.
+• Strong problem-solving and analytical skills ",2026,Bachelors,1-5,"Python, ML, LLMS, APIs, AWS/Azure, SQL, CI/CD, TensorFlow/Pytorch, Scikit-Learn","Communication, Problem Solving"
+76,AI Engineer,Junior,"Hands-on experience with
+LLMs and Agentic AI frameworks
+Strong proficiency in
+Python
+and AI application development
+Experience with
+LangChain, LangGraph, AutoGen, CrewAI, OpenAI APIs, MCP
+Knowledge of
+RAG, vector databases, prompt engineering, tool usage, memory architectures
+Exposure to
+CI/CD, DevOps, DevSecOps workflows
+Experience integrating AI into
+developer platforms and enterprise workflows
+Understanding of
+security, governance, and scalable AI deployment
+Preferred:
+Experience with
+GitHub Copilot, Claude, Codex
+Exposure to
+cloud platforms (AWS / Azure / GCP)
+Experience building
+developer productivity platforms ",2026,Bachelors,0-1,"Python, LLMs, ML, Agents, LangChain, LangGraph, AutoGen, CrewAI, OpenAI, APIs, MCP, RAG, VectorDB, CI/CD, Git, Github, AWS/Azure","Communication, Problem Solving"
+77,AI Engineer,Junior,"• Bachelor’s or Master’s in Computer Science, AI, Data Science, or related field
+Experience
+• 2–5 years of hands-on experience in AI/ML or applied AI engineering
+• Experience building end-to-end AI systems (not just experimentation)
+• Exposure to LLMs and AI agents in production environments
+Technical Skills (Must-Have)
+• Strong Python programming skills
+• Experience with LLMs (OpenAI, open-source models, etc.)
+• Understanding of agent-based systems and tool integration
+• Experience with APIs, microservices, and system integration
+• Familiarity with cloud platforms (preferably GCP)
+• Knowledge of software engineering best practices (testing, version control)
+Preferred Skills (Good to Have)
+• Experience with agent frameworks (LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel)
+• Knowledge of RAG architectures and vector databases (Pinecone, ChromaDB, etc.)
+• Familiarity with MLOps tools (Docker, CI/CD, model serving frameworks)
+• Experience with structured outputs and function calling
+• Exposure to CAE/FEA tools (ANSYS, Abaqus, LS-DYNA)
+Core Competencies
+• Agentic system design (planning, memory, orchestration)
+• Prompt engineering and LLM optimisation
+• Reliability engineering and AI safety practices
+• Strong analytical thinking and problem-solving
+• Effective cross-functional communication ",2026,Bachelors/Masters,1-5,"Python, ML, LLMs, AWS/Azure, APIs, Git, Github, LangChain, LangGraph, AutoGen, CrewAI, RAG, Docker, CI/CD, System Design, Prompt Engineering","Communication, Problem Solving, Analytical Skills"
+84,AI Engineer,Junior,"• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field; or High School Diploma/General Education Degree and 4+ years of relevant as outlined in the essential duties in lieu of Bachelor’s Degree.
+• Professional experience in AI/ML model development.
+• Demonstrated ability working with machine learning frameworks, programming languages like Python, and cloud platforms.
+• Demonstrated ability to learn new technologies.
+• Demonstrated understanding of ethical considerations in AI systems.
+• Strong analytical and problem-solving skills with understanding of AI/ML techniques.
+Preferred Qualifications:
+• Experience deploying Gen AI solutions at scale.
+• Experience fine tuning LLMs, SLMs, teacher-student frameworks and model distillation.
+• Familiarity with human in the loop methods for aligning LLMs with human preferences.
+• Familiarity with agentic framework platforms and concepts. Experience deploying agentic-based solutions is a plus. ",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, GenAI, LLMs, ","Communication, Problem Solving"
+89,AI Engineer,Junior,"M.Tech (CS/IT) - Mandatory- Freshers (0 yrs) OR 1-2 years of experience in AI/ML- Strong interest in AI, machine learning, and automationKey Responsibilities : Build AI Solutions : - Develop AI/ML models and GenAI applications using LLMs- Build RAG pipelines, NLP models, and automation workflows- Work on real-world use cases across insurance & operationsCoding & Development (Core Focus) : - Write clean, scalable code using Python and ML frameworks- Work with HuggingFace, PyTorch, LangChain, APIs, and SQL- Design and implement end-to-end AI workflowsExperiment & Learn : - Work on prompt engineering, fine-tuning, and model optimisation- Explore techniques like LoRA / QLoRA, embeddings, vector DBs- Continuously experiment with new AI approaches and toolsDeployment & Integration : - Assist in deploying models using basic MLOps practices- Integrate AI solutions with internal systems via APIs and data pipelinesDrive Business Impact : - Understand business problems and convert them into AI use cases- Deliver measurable impact like: Process automation, TAT reduction, Efficiency improvement ",2026,Masters,1-5,"Python, ML, MLOps, Git, Github, LLMs, NLP, RAG, Agents, HuggingFace, TensorFlow/PyTorch, LangChain, APIs, SQL, VectorDB","Communication, Problem Solving"
+94,AI Engineer,Junior,"• Strong foundation in Computer Science and Software Development, including data structures, algorithms, and version control.
+• Experience with Pattern Recognition and Neural Networks for real-world applications such as classification, prediction, and recommendation systems.
+• Hands-on expertise in Natural Language Processing (NLP), including text analysis, conversational interfaces, and language models.
+• Proficiency with programming languages commonly used in AI (such as Python or JavaScript) and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
+• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.
+• Ability to work collaboratively on-site, communicate complex technical concepts clearly, and translate business needs into AI solutions.
+• Experience deploying AI models into production environments and optimizing for scalability and performance is a plus.
+• Familiarity with cloud platforms, APIs, and MLOps practices for model monitoring and continuous improvement is beneficial. ",2026,Bachelors/Masters,0-1,"Python, NLP, TensorFlow/PyTorch, Scikit-Learn, APIs, MLOps","Communication, Problem Solving"
+101,AI Engineer,Junior,"• Assist in collecting, cleaning, and preprocessing datasets for ML models
+• Build, train, and evaluate machine learning and deep learning models
+• Support development and integration of AI features into existing products
+• Work with frameworks like TensorFlow, PyTorch, or Scikit-learn
+• Conduct exploratory data analysis (EDA) and document findings
+• Help fine-tune and experiment with LLMs/NLP models (if applicable)
+• Write clean, efficient, and well-documented Python code
+• Collaborate with senior data scientists/engineers to understand business requirements
+• Stay updated with the latest AI/ML research, tools, and best practices
+Required Skills
+• Strong foundation in Python programming
+• Good understanding of Machine Learning concepts (supervised/unsupervised learning, regression, classification, clustering)
+• Familiarity with libraries such as NumPy, Pandas, Scikit-learn
+• Basic knowledge of Deep Learning (Neural Networks, CNNs, RNNs) is a plus
+• Understanding of statistics and probability
+• Familiarity with SQL and data handling
+• Basic knowledge of Git/GitHub for version control ",2026,Not Specified,0-1,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, LLMs, NLP, NumPy, Pandas, SQL, Git, Github","Communication, Problem Solving"
+107,AI Engineer,Junior,"Strong understanding of AI/ML fundamentals, model development, and deployment strategies.
+Hands-on experience training and fine-tuning models (e.g., regression, classification, ranking, NLP).
+Familiarity with AdTech systems such as SSP, DSP, DMP, and RTB (Real-Time Bidding).
+Experience with AWS AI/ML services (SageMaker, Comprehend, Bedrock, etc.) or other cloud ML platforms.
+Proficiency in Python, TensorFlow, PyTorch, or similar frameworks.
+Ability to analyze business and campaign data and convert them into scalable AI solutions.
+Strong problem-solving skills, analytical mindset, and attention to detail.
+Good to Have (Optional):
+AWS Machine Learning Specialty or AI Practitioner certifications.
+Experience with RAG systems, LLMs, or Generative AI for AdTech use cases.
+Knowledge of MLOps and CI/CD pipelines for model deployment.
+Exposure automated campaign optimization, bid strategy modeling, or user segmentation algorithms 
+108,AI Engineer,Junior,"Strong foundation in Computer Science and Software Development, including data structures, algorithms, and version control.Experience with Pattern Recognition and Neural Networks for real-world applications such as classification, prediction, and recommendation systems.Hands-on expertise in Natural Language Processing (NLP), including text analysis, conversational interfaces, and language models.Proficiency with programming languages commonly used in AI (such as Python or JavaScript) and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.Ability to work collaboratively on-site, communicate complex technical concepts clearly, and translate business needs into AI solutions.Experience deploying AI models into production environments and optimizing for scalability and performance is a plus.Familiarity with cloud platforms, APIs, and MLOps practices for model monitoring and continuous improvement is beneficial. ",2026,Bachelors/Masters,0-1,"Python, ML, NLP, Javascript, TensorFlow/PyTorch, Scikit-Learn, APUIs, MLOps, CI/CD","Communication, Problem Solving"
+109,AI Engineer,Junior,"• Bachelor’s Degree in IT or equivalent Computer Science, Machine Learning, or related field.
+• 5-8 years of professional experience in software development; you will be able to discuss in depth both the design and your significant contributions to one or more projects.
+• Experience with open-source large language models and fine-tuning at scale
+• Familiarity with vector databases, embedding models, and semantic search techniques
+• Background in natural language processing (NLP) and understanding of transformer architecture internals
+• Experience with model deployment, monitoring, and A/B testing in production environments
+• Knowledge of responsible AI practices, including bias detection, fairness evaluation, and explainability
+• Advanced expertise in enterprise automation frameworks and RPA (Robotic Process Automation) integration
+• Experience with intelligent document understanding (IDP) platforms and layout analysis models
+• Deep expertise in Oracle Cloud ecosystem, including OIC, VBCS, and APEX.
+• Experience developing custom adapters and AI-connectors for OIC to integrate third-party systems
+• Advanced PL/SQL performance tuning and database optimization on Oracle Database
+• Certification in Oracle Cloud technologies (Oracle AI related, Integration Cloud, Oracle PAAS)
+• Custom Role Development and Cloud System Administration services
+• Good knowledge in any of (Order to Cash) or (Procure to Pay) custom development experience in automated AR/AP Invoices or Bank Statement integration
+• Hands-on knowledge of Security roles in Fusion, page personalization, and Web Services is a definite plus.
+• Determination, self-motivation, and an eagerness to take on new challenges.
+• Ability to adapt quickly, working in a dynamic business environment.
+• Excellent analytical and problem-solving skills. ",2026,Bachelors,0-1,"Python, ML, NLP, SQL","Communication, Problem Solving"
+110,AI Engineer,Junior,"• Strong programming skills in Python.
+• Experience with machine learning frameworks such as:
+o TensorFlow
+o PyTorch
+o Scikit-learn
+• Knowledge of deep learning architectures (CNN, RNN, Transformers).
+• Experience with data processing tools such as Pandas, NumPy, and Spark.
+• Familiarity with model deployment using Docker, FastAPI, or Flask.
+• Understanding of MLOps practices.
+• Experience with cloud platforms such as AWS, GCP, or Azure.
+• Knowledge of Git and CI/CD pipelines.
+Preferred Qualifications:
+• Experience with LLMs and Generative AI.
+• Knowledge of vector databases and embeddings.
+• Familiarity with LangChain or LLM orchestration frameworks.
+• Experience building AI-powered APIs or chatbots.
+• Exposure to Kubernetes and scalable ML infrastructure.
+Education
+• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field. ",2026,Bachelors/Masters,0-1,"Python. ML, LLMs, TensorFlow/PyTorch, Scikit-Learn, Pandas, NumPy, APIs, Docker, MLOps, Git, Github, CI/CD, AWS/Azure, GenAI, LangChain, LangGraph, LlamaIndex, Agents, GenAI, Kubernetes, ","Communication, Problem Solving"
+112,AI Engineer,Junior,"• Bachelor's degree in Computer Science, Data Science, AI/ML, or a related field (or final-year student/intern).
+• Strong foundation in Java and Python and familiarity with ML libraries like scikit-learn, TensorFlow, or PyTorch.
+• Basic understanding of LLMs and their applications (e. g., chatbots, text classification, summarization), openAI or claude.
+• Exposure to data analysis tools like Pandas, NumPy, and SQL.
+• Familiarity with Git and version control practices.
+• Willingness to learn and contribute in a fast-paced, collaborative environment.
+• Academic or personal projects involving ML/AI or NLP.
+• Experience with cloud platforms (AWS, GCP, or Azure) or Docker.
+• Exposure to tools like LangChain, Hugging Face Transformers, or vector databases.
+• Participation in AI/ML competitions (e. g., Kaggle) or open-source contributions. ",2026,Bachelors,0-1,"Python, ML, Java, Pandas, NumPy, SQL, Git, Github, NLP, AWS/Azure, Docker, LangChain, LangGraph, Agents, OpenAI, LLMs, TensorFlow/Pytorch, Scikit-Learn","Communication, Problem Solving"
+113,AI Developer,Junior,"1. 1-2 years of software engineering experience, ideally in a product-focused or startup environment. 2. Strong Python skills: You write clean, maintainable code and have experience with modern backend frameworks. 3. Database Fundamentals: Comfortable writing SQL and working with relational databases (especially PostgreSQL). You aren't afraid of complex queries or working with JSON/JSONB data types. 4. AI/ML Basics: Practical experience working with LLM APIs (OpenAI, Anthropic, etc.) and a foundational understanding of text embeddings, tokenization, and semantic search. ",2026,Bachelors,0-1,"Python, SQL, APIs, OpenAI, LLMs","Communication, Problem Solving"
+114,AI Engineer,Junior,"- Minimum bachelors degree in computer science, Mathematics, Engineering, Statistics, or a related field.
+- At least 1 year of experience in Natural Language Processing (NLP), Machine Learning, Generative AI specifically with Large Language Models (LLM).
+- Proficiency in Python and other applicable full-stack software programming languages.
+- Strong knowledge of machine learning, language modeling, data mining, and predictive modeling.
+- Excellent understanding of data science algorithms, processes, tools, and platforms.
+- Strong problem-solving mindset, with the ability to work in ambiguous and fast-paced environments.
+- Knowledge of API integration, containerization (e.g., Docker), cloud platforms (e.g., Azure, AWS, GCP), automated testing frameworks, and CI/CD practices. ",2026,Bachelors,0-1,"Python, NLP, ML, APIs, Docker, AWS/Azure, CI/CD","Communication, Problem Solving"
+115,AI Engineer,Junior,"• Bachelor's degree in Computer Science, Data Science, AI/ML, or a related field (or final-year student/intern).
+• Strong foundation in Java and Python and familiarity with ML libraries like scikit-learn, TensorFlow, or PyTorch.
+• Basic understanding of LLMs and their applications (e. g., chatbots, text classification, summarization), openAI or claude.
+• Exposure to data analysis tools like Pandas, NumPy, and SQL.
+• Familiarity with Git and version control practices.
+• Willingness to learn and contribute in a fast-paced, collaborative environment.
+• Academic or personal projects involving ML/AI or NLP.
+• Experience with cloud platforms (AWS, GCP, or Azure) or Docker.
+• Exposure to tools like LangChain, Hugging Face Transformers, or vector databases.
+• Participation in AI/ML competitions (e. g., Kaggle) or open-source contributions ",2026,Bachelors,0-1,"Python, NLP, SQL, Git, Github, Pandas, NumPy, TensorFlow/PyTorch, Scikit-Learn, LLMs, OpenAI, AWS/Azure, Docker, LangChain, LangGraph, Hugging Face, VectorDB","Communication, Problem Solving"
+117,AI Engineer,Junior,"Solid programming experience in Python / R / C / C++ .
+Robust understanding of:
+Machine Learning algorithms
+Deep Learning architectures
+Model evaluation techniques
+Data preprocessing
+Hands-on experience with:
+TensorFlow
+Keras
+PyTorch
+Experience working with Computer Vision, NLP, and Predictive Analytics projects.
+Solid problem-solving and analytical skills.
+Ability to convert business problems into AI/ML solutions.
+Experience deploying ML models into production environments.
+Knowledge of MLOps, APIs, cloud platforms, or model monitoring is a plus.
+118,AI Engineer,Junior,"Strong understanding of
+AI agents
+and experience in building agents/skills
+Hands-on experience with
+LLM integration
+and advanced prompt engineering
+Expertise in
+time-series forecasting
+or predictive modeling (preferably in automotive/fleet domains)
+Proficiency in Python ML ecosystem:
+scikit-learn, pandas , and ideally
+PyTorch/TensorFlow
+Solid knowledge of
+RAG (Retrieval-Augmented Generation)
+frameworks
+Experience in
+model evaluation , experimentation, and A/B testing 
+119,AI Engineer,Junior,"• Strong production-level software engineering skills, with depth in either Python/backend systems or React/TypeScript/frontend systems, and willingness to work across both
+• Ability to take clear product goals, make good technical decisions, and ship reliable software without heavy process
+• Experience using AI coding tools such as Cursor, Claude Code, or similar tools in real development work
+• Genuine interest in AI systems and hardware design
+• Clear written and verbal communication
+• Experience with LLM applications, agents, evals, LangChain, tool use, or prompt engineering
+• Experience building desktop apps, Electron apps, complex frontend state, or developer tools
+• Hardware project experience: robots, drones, embedded systems, PCBs, Formula Student, KiCad/Altium, firmware, or electronics prototyping
+• ECE or CS background, or equivalent demonstrated experience across software and hardware
+• Examples of shipped products, side projects, open-source work, research papers, or technical demos you can walk us through ",2026,Bachelors,0-1,"Python, React, LLMs, Agents, LangChain, LangGraph, LlamaIndex, Prompt Engineering","Communication, Problem Solving"
+121,AI Engineer,Junior,"Generative AI & NLP Expertise: Extensive experience in developing and deploying Generative AI applications and NLP frameworks, with hands-on knowledge of LLM fine-tuning, model customization, and AI-powered automation.
+Hands-On Data Science Experience: 4+ years of experience in data science, with a proven ability to build and operationalize machine learning and NLP models in real-world environments.
+AI Innovation: Deep knowledge of the latest developments in Generative AI and NLP, with a passion for experimenting with cutting-edge research and incorporating it into practical solutions.
+Problem-Solving Mindset: Strong analytical skills and a solution-oriented approach to applying data science techniques to complex business problems.
+Communication Skills: Exceptional ability to translate technical AI concepts into business insights and recommendations for non-technical stakeholders.",2026,Bachelors,0-1,"Python, ML, NLP, GenAI, LLMs","Communication, Problem Solving"
+123,AI Engineer,Junior,"• Minimum 1 year of hands-on experience building AI use cases
+• Proven experience creating multiple AI workflows
+• Experience building or working with AI agents and agentic workflows
+• Strong understanding of Large Language Models and their practical applications
+• Good knowledge of Retrieval-Augmented Generation
+• Strong proficiency in Python
+• Experience connecting AI models with APIs, databases, documents or business systems
+• Ability to take a requirement from idea to working solution
+• Understanding of prompt engineering, structured outputs and function or tool calling
+• Ability to independently take a business requirement and convert it into a working AI solution
+• Strong problem-solving and experimentation skills
+What Matters Most
+We are specifically looking for someone who can demonstrate:
+• Workflows they have personally built
+• AI agents they have worked with or developed
+• How they have used LLMs in practical applications
+• The business problem solved and the final outcome 
+124,AI Developer,Junior,"• 1+ years of experience in Generative AI or LLM application development.
+• Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
+• Strong Python programming skills.
+• Good understanding of APIs, JSON, vector databases, and embeddings.
+• Familiarity with prompt engineering and RAG concepts.
+• Passion for building real-world AI products.
+Good to Have
+• Experience with LangSmith.
+• Knowledge of MCP, tool calling, and AI orchestration.
+• Experience with Azure AI, OpenAI, or Anthropic APIs.
+• Knowledge of Docker and cloud deployment.
+• Experience using Cursor, Codex, or Claude Code. 
+125,AI Engineer,Junior,"• Strong experience with React.js, Next.js, Node.js, TypeScript, Python, FastAPI, REST APIs, SQL/NoSQL databases, and Git.
+• Understanding of Machine Learning algorithms, model deployment, and software development best practices.
+• Experience with OpenAI, Gemini, Claude, and similar AI/ML frameworks.
+• Familiarity with LangChain, LangGraph, RAG, Vector Databases, Prompt Engineering, and AI Agents.
+• Experience using GitHub Copilot, Cursor, Claude Code, or similar AI development tools.
+Preferred Skills
+• Experience with AWS/GCP/Azure, MLOps, and cloud deployment.
+• Strong analytical thinking, debugging, and problem-solving skills. ",2026,Bachelors,0-1,"Python, SQL, Javascript, React, APIs, Git, Github, ML, Agents, OpenAI, LangChain, LangGraph, VectorDB, RAG, Prompt Engineering, AWS/Azure, MLOps","Communication, Problem Solving"
+126,AI Engineer,Junior,"Strong experience with machine learning and natural language processing.
+Experience working with large language models (LLMs), prompt engineering, retrieval-augmented systems, or conversational AI.
+Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
+Experience developing mobile or cross-platform applications.
+Understanding of healthcare data privacy, security, and ethical AI principles.
+Ability to work effectively in multidisciplinary clinical and technical teams.
+Preferred Qualifications
+Experience in digital health, health technology, medical devices, or assistive technologies.
+Familiarity with speech-language pathology, aphasia, neuro-oncology, or neurological disorders.
+Experience with user-centered design and accessibility-focused product development.
+Knowledge of clinical research methodologies and healthcare regulations.
+Experience deploying AI systems in real-world healthcare environments. ",2026,Bachelors,0-1,"Python, ML, Prompt Engineering, LLMs, RAG, GenAI, TensorFlow/PyTorch","Communication, Problem Solving"
+128,AI Engineer,Junior,"• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field; or High School Diploma/General Education Degree and 4+ years of relevant as outlined in the essential duties in lieu of Bachelor’s Degree.
+• Professional experience in AI/ML model development.
+• Demonstrated ability working with machine learning frameworks, programming languages like Python, and cloud platforms.
+• Demonstrated ability to learn new technologies.
+• Demonstrated understanding of ethical considerations in AI systems.
+• Strong analytical and problem-solving skills with understanding of AI/ML techniques.
+Preferred Qualifications:
+• Experience deploying Gen AI solutions at scale.
+• Experience fine tuning LLMs, SLMs, teacher-student frameworks and model distillation.
+• Familiarity with human in the loop methods for aligning LLMs with human preferences.
+• Familiarity with agentic framework platforms and concepts. Experience deploying agentic-based solutions is a plus. ",2026,Bachelors,0-1,"Python, ML, GenAI, LLMs","Communication, Problem Solving"
+129,AI Developer,Junior,"Node.js / Express · Claude API (Anthropic) · Supabase · Wati (WhatsApp Business API) · node-cron · Jest · DigitalOcean VPS
+You're right for this if you:
+• Have shipped production Node.js APIs that real users hit
+• Are comfortable with webhooks, async JavaScript, and third-party API integrations
+• Have worked with PostgreSQL or Supabase
+• Can deploy a backend to a VPS without hand-holding
+• Write tests and don't consider them optional
+• (Bonus if you've built with Claude / OpenAI or WhatsApp Business API before) 
+130,AI Engineer,Junior,"• 0–4 years of experience in Machine Learning, NLP, Speech AI, or Applied AI.
+• Strong proficiency in Python.
+• Experience with PyTorch, TensorFlow, or similar ML frameworks.
+• Knowledge of NLP frameworks such as Hugging Face, spaCy, or NLTK.
+• Understanding of model training, evaluation, and deployment.
+• Strong analytical and problem-solving skills.
+Good to Have
+• Experience with Whisper, Wav2Vec2, Kaldi, DeepSpeech, or similar speech technologies.
+• Experience with LLMs and Generative AI applications.
+• Familiarity with FastAPI, Docker, and cloud platforms (AWS/GCP/Azure).
+• Exposure to MLOps and production ML systems.
+• Understanding of language assessment, educational testing, or communication evaluation platforms. ",2026,Bachelors,0-1,"Python, ML, NLP, TensorFlow/PyTorch, Huging Face, LLMs, GenAI, APIs, Docker, AWS/Azure, MLOps","Communication, Problem Solving"
+131,AI Engineer,Junior,"Strong understanding of Python
+Basic knowledge of Machine Learning concepts
+Familiarity with libraries like NumPy, Pandas, Scikit-learn
+Understanding of data preprocessing and model evaluation
+Basic knowledge of NLP, Computer Vision, or Generative AI
+Ability to work with APIs and AI tools
+Positive analytical and problem-solving skills
+Valuable to Have
+Knowledge of TensorFlow or PyTorch
+Experience with OpenAI APIs or other LLM tools
+Basic understanding of SQL and databases
+Experience with college projects, internships, or GitHub projects
+Knowledge of automation tools and AI agents
+Eligibility Criteria
+Bachelor’s degree in:
+Computer Science
+BCA / MCA
+B.Tech / M.Tech
+Artificial Intelligence
+Data Science
+Mathematics
+Statistics
+Or related fields 
+133,AI Engineer,Junior,"• Python
+• LangChain
+• OpenAI / Anthropic APIs
+• Prompt Engineering
+• Vector Databases (Basic)
+• FastAPI
+• Git
+• PostgreSQL 
+135,AI Engineer,Junior,"• * Education: Bachelors degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience).
+• * Familiarity with AI/ML Concepts: Basic understanding of artificial intelligence, machine learning, and data science.
+• * Attention to Detail: Strong focus on data accuracy, precision, and consistency.
+• * Technical Skills: Proficiency with spreadsheets (Excel/Google Sheets) and data processing tools.
+• * Communication Skills: Strong written and verbal communication skills to document processes and work with cross-functional teams.
+• * Problem-Solving Abilities: Ability to identify challenges in data and propose efficient solutions.
+• * Tech-Savvy: Willingness to learn and adapt to new tools and technologies relevant to AI/ML projects.
+• Experience:
+• * Entry-level position ideal for recent graduates or individuals with a passion for AI/ML.
+• * Previous experience in data annotation, data entry, or any technical support role is a plus but not mandatory.
+• Working Hours:
+• * Full-time (40 hours per week).
+• * Flexible working hours to accommodate global team collaboration.
+• * Remote work opportunity with potential for occasional team meetings via video calls.
+• Knowledge, Skills, and Abilities:
+• * Knowledge of Data Preparation: Basic understanding of data cleaning, normalization, and preprocessing for machine learning models.
+• * Analytical Skills: Ability to analyze and manipulate datasets to extract meaningful insights.
+• * Familiarity with AI Tools: Exposure to basic AI tools and platforms such as TensorFlow, PyTorch, or similar technologies is beneficial.
+• * Adaptability: Willingness to learn and grow within the dynamic field of AI/ML.
+• * Team Collaboration: Ability to work effectively in a remote, collaborative environment.
+• Benefits:
+• * Competitive Salary: Competitive pay based on experience and skill level.
+• * Learning and Development: Access to training resources, mentorship, and opportunities to grow within the AI/ML field.
+• * Remote Work Flexibility: Work from the comfort of your home with flexible hours.
+• * Health and Wellness Benefits: Comprehensive health insurance and wellness programs.
+• * Career Growth: Opportunity for advancement in a rapidly growing industry.
+• * Team Collaboration: Work alongside highly skilled professionals in a supportive, remote work environment. ",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, GenAI, LLMs","Communication, Problem Solving"
+142,AI Developer,Junior,"Job DescriptionAre you passionate about Python and curious about AI/ML?Join us to kickstart your career with hands-on experience in real-world machine learning projects!What Youll Work OnPython coding for AI/ML applicationsData preprocessing, model training & deploymentCollaborate with engineers and analysts on end-to-end AI solutionsExplore data and visualize insights using popular Python librariesPreferred SkillsStrong Python fundamentalsBasic ML concepts & libraries (NumPy, Pandas, Scikit-learn)Aptitude for problem-solving & statisticsFamiliarity with tools like Git, Matplotlib, or Seaborn is a plusConsistent academic performance with 70% or equivalent and above throughoutRequirementsAre you passionate about Python and curious about AI/ML? Join us to kickstart your career with hands-on experience in real-world machine learning projects! What youll work on: Python coding for AI/ML applications Data preprocessing, model training & deployment Collaborate with engineers and analysts on end-to-end AI solutions Explore data and visualize insights using popular Python libraries Preferred Skills Strong Python fundamentals Basic ML concepts & libraries (NumPy, Pandas, Scikit-learn) Aptitude for problem-solving & statistics Familiarity with tools like Git, Matplotlib, or Seaborn is a plus Consistent academic performance with 70% or equivalent and above throughout ",2026,Bachelors,0-1,"Python, ML, NumPy, Pandas, Scikit-Learn, APIs, Git, Github","Communication, Problem Solving"
+143,AI Developer,Junior,"• Strong programming skills in Python (FastAPI, Flask) or Node.js.
+• Exposure to NLP, LLMs, AI APIs (ChatGPT, Perplexity.ai, LangChain).
+• Familiarity with RESTful APIs and Graph Databases (Neo4j).
+• Basic understanding of cloud platforms (AWS, Azure, GCP).
+• Passion for AI, NLP, and chatbot development.
+• Bonus: Knowledge of UI frameworks (React, Next.js).
+• Good to have - Pinecone or equivalent vector databases. ",2026,Bachelors,0-1,"Python, ML, APIs, LLMs, NLP, AWS/Azure, VectorDB","Communication, Problem Solving"
+144,AI Developer,Junior,"The ideal candidate will be responsible for developing and debugging responsive web applications for the company. Using Python, Django, JavaScript, this candidate will be able to translate user and business needs into functional products. Must have knowledge in PythonDjangoExperience in Gen-AI APIs, RAGDatabase schema modeling and designingBasics in CSS, Bootstrap, Bulma etcTools like web-pack, npm, yarn etc.Good sense of designVersion controlling and GitHub ",2026,Bachelors,0-1,"Python, APIs, Django, Javascript, GenAI, RAG, SQL, Git, Github","Comunication, Problem Solving"
+172,AI Developer,Junior,"We are looking for a passionate Junior AI Automation Engineer to build AI-powered automation systems using open-source technologies. You will work on AI agents, browser automation, backend APIs, and workflow automation—not UI/UX development. Strong knowledge of Python, FastAPI, GitHub, Railway, Vercel, Playwright, REST APIs, and PostgreSQL is required. Experience with LLMs (OpenAI/Claude/Gemini), LangChain/LangGraph, n8n, Docker, MCP, or RAG is a plus. You should be comfortable integrating APIs, deploying applications, and solving real-world business problems through automation. We value hands-on builders with working GitHub projects over certifications. Fresh ideas, curiosity, and a willingness to learn are essential. ",2026,Bachelors,0-1,"Python, ML, SQL, APIs, LLMs, n8n, Agents, LangChain, LangGraph, Docker, MCP, RAG, Github, Git","Communication, Problem Solving"
+173,AI Developer,Junior,"• * 1–2 years of hands-on experience in Python AI/ML development.
+• Strong understanding of core Python concepts, data structures, and algorithms.
+• Experience with frameworks such as Django, Flask, or FastAPI.
+• Familiarity with RESTful APIs and microservices architecture.
+• Good understanding of databases (MySQL, PostgreSQL, or NoSQL).
+• Experience with version control systems like Git.
+• Strong debugging and problem-solving skills.
+• Strong communication and collaboration skills.
+• Exposure to AI/ML concepts or AI-assisted development (e.g., prompt engineering, AI coding tools).
+• Experience working on international/global projects.
+• Familiarity with cloud platforms (AWS, Azure, or GCP).
+• Knowledge of containerization tools like Docker.
+• Understanding of CI/CD pipelines and DevOps practices. ",2026,Bachelors,0-1,"Python, ML, APIs, Django, SQL, Git, Github, AWS/Azure, Docker, CI/CD, Prompt Engineering","Communication, Problem Solving"
+174,AI Developer,Junior,"Required Qualifications
+Strong experience with machine learning and natural language processing.
+Experience working with large language models (LLMs), prompt engineering, retrieval-augmented systems, or conversational AI.
+Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
+Experience developing mobile or cross-platform applications.
+Understanding of healthcare data privacy, security, and ethical AI principles.
+Ability to work effectively in multidisciplinary clinical and technical teams.
+Preferred Qualifications
+Experience in digital health, health technology, medical devices, or assistive technologies.
+Familiarity with speech-language pathology, aphasia, neuro-oncology, or neurological disorders.
+Experience with user-centered design and accessibility-focused product development.
+Knowledge of clinical research methodologies and healthcare regulations.
+Experience deploying AI systems in real-world healthcare environments. ",2026,Bachelors,0-1,"Python, GenAI, LLMs, Agents, LangChain, OpenAI, RAG, VectorDB, NLP, Prompt Engineering, TensorFlow/PyTorch, ","Communication, Problem Solving"
+175,AI Developer,Junior,"Required Skills & Qualifications:
+• Strong logical and analytical thinking.
+• Good communication and collaboration skills.
+• Quick learner with a strong willingness to upskill.
+• Strong Python programming skills (loops, OOP, libraries).
+• Basic understanding of Artificial Intelligence and Machine Learning concepts.
+• Familiarity with libraries such as NumPy, Pandas, Matplotlib, scikit-learn, or TensorFlow/PyTorch (basic level).
+• Understanding of APIs and how to integrate them.
+• Knowledge of chatbot development tools or frameworks is a plus (e.g., Rasa, LangChain, OpenAI API).
+• Strong problem-solving and analytical skills.
+• Eagerness to learn new AI technologies and tools.
+Preferred (But Not Mandatory):
+• Knowledge of chatbot frameworks (e.g., Rasa, LangChain, Dialogflow).
+• Experience with AI data visualization tools or dashboard development.
+• Awareness of Natural Language Processing (NLP) concepts. ",2026,Bachelors,0-1,"Python, ML, Pandas, NumPy, Scikit-Learn, TensorFlow/PyTorch, APIs, Agents, LangChain, NLP, OpenAI","Communication, Problem Solving"
+176,AI Developer,Junior,"Design, train, and fine-tune AI/ML models using Python frameworks. Work on LLMs, prompt engineering, data preprocessing, and model evaluation. Develop AI-based applications integrating NLP, computer vision, or generative content systems.
+Required Candidate profile
+Strong understanding of Python, ML, and deep learning concepts. Familiar with Generative AI tools (OpenAI, Hugging Face, LangChain, etc.). Eager to explore LLMs and prompt-based systems. ",2026,Bachelors,0-1,"Python, LLMs, NLP, Prompt Engineering, ML, GenAI, OpenAI, Hugging Face, LangChain","Communication, Problem Solving"
+183,AI Developer,Junior,"1-2 years of software engineering experience, ideally in a product-focused or startup environment. 2. Strong Python skills: You write clean, maintainable code and have experience with modern backend frameworks. 3. Database Fundamentals: Comfortable writing SQL and working with relational databases (especially PostgreSQL). You aren't afraid of complex queries or working with JSON/JSONB data types. 4. AI/ML Basics: Practical experience working with LLM APIs (OpenAI, Anthropic, etc.) and a foundational understanding of text embeddings, tokenization, and semantic search. ",2026,Bachelors,0-1,"Python, ML, SQL. LLMs, APIs, OpenAI","Communication, Problem Solving"
+184,AI Developer,Junior,"Requirements: Backend development experience with Python, including exposure to building or consuming APIs.
+Foundational knowledge of LLMs, AI agents, RAG systems, or ML-driven applications, including hands-on project or coursework experience.
+Familiarity with cloud platforms, preferably Azure.
+Basic understanding of data security, governance, and reliability principles.
+Ability to write clean, maintainable code and collaborate within a team environment.
+Good communication skills and a willingness to learn in a fast-moving technical domain.
+Nice to have: Exposure to financial services, enterprise data, or data-heavy domains is a plus.
+Interest in semantic data modeling or knowledge graphs. Any experience with workflow automation tools or rules engines.
+Awareness of enterprise AI governance and compliance considerations.",2026,Bachelors,0-1,"Python, ML, LLMs, RAG, Agents, LangChain, LangGraph, AWS/Azure, n8n","Communication, Problem Solving"
+191,AI Developer,Junior,"Education:
+Bachelor s degree in Engineering, Computer Science, Data Science, Gen AI or related fields. Final-year students or recent graduates are welcome to apply.
+Technical Skills:
+Strong foundation in Java, React, NodeJS, Python, SQL, and Excel
+Basic understanding of data structures, databases, and algorithms
+Exposure to pandas, NumPy, PySpark, scikit-learn, GenAI, Agentic AI or TensorFlow is a plus
+Familiarity with BI tools (e.g., Power BI, Tableau) or cloud platforms (e.g., AWS, GCP) is desirable
+Knowledge of version control (Git) is an advantage
+Soft Skills
+
+Curiosity and a passion for data-driven problem solving
+Strong analytical and logical thinking
+Good communication and collaboration skills
+Willingness to learn in a fast-paced environment
+Ability to break down complex problems and document clearly
+Preferred (Good to Have, Not Mandatory)
+
+Internship or academic project in data analytics, machine learning, or database systems
+Participation in hackathons, coding contests, or Kaggle competitions
+Exposure to Agile or collaborative tools like JIRA, Confluence",2026,Bachelors,0-1,"Python, Java, React, SQL, NumPy,Scikit-Learn, Javascript, GenAI, Agents, LangChain, LangGraph, Github, Github TensorFlow/PyTorch, AWS/Azure","Communication, Problem Solving"
+192,AI Developer,Junior,"Work on AI applications involving NLP, Computer Vision, and Predictive Analytics.
+Collaborate with senior developers to implement AI-driven solutions.
+Perform data analysis and generate actionable insights.
+Test, debug, and optimize AI/ML models for performance and accuracy.
+Stay updated with the latest advancements in AI, Machine Learning, and Generative AI.
+Required Skills Basic knowledge of Python programming.
+Understanding of Machine Learning algorithms and concepts.
+Familiarity with libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
+Basic understanding of Data Structures and Algorithms.
+Knowledge of SQL and database concepts.
+Strong analytical and problem-solving skills.
+Good communication and teamwork abilities. ",2026,Bachelors,0-1,"Python, ML, NLP, GenAI, SQL, TensorFlow/PyTorch, Scikit-Learn, NumPy, Pandas, ","Communication, Problem Solving"
+193,AI Developer,Junior,"Strong programming skills in Python (FastAPI, Flask) or Node.js.
+Exposure to NLP, LLMs, AI APIs (ChatGPT, Perplexity.ai, LangChain).
+Familiarity with RESTful APIs and Graph Databases (Neo4j).
+Basic understanding of cloud platforms (AWS, Azure, GCP).
+Passion for AI, NLP, and chatbot development.
+Bonus: Knowledge of UI frameworks (React, Next.js).
+Good to have - Pinecone or equivalent vector databases.
+198,AI Developer,Junior,"Design, develop, and implement state-of-the-art generative AI models, including Large Language Models (LLMs), Diffusion Models, GANs, and VAEs, for various applications.
+Research and evaluate new generative AI techniques and frameworks to identify opportunities for innovation and improvement.
+Optimize and fine-tune existing generative models for performance, efficiency, and scalability.
+Integrate generative AI solutions into existing product pipelines and develop new APIs for seamless interaction.
+Collaborate with data scientists, machine learning engineers, and product managers to define requirements, design solutions, and deliver high-quality AI-powered features.
+Develop robust MLOps practices for deploying, monitoring, and maintaining generative AI models in production environments.
+Conduct rigorous testing, validation, and evaluation of models to ensure accuracy, reliability, and ethical compliance.
+Stay abreast of the latest research and developments in generative AI and machine learning, applying relevant insights to ongoing projects.
+Document technical designs, model architectures, and implementation details clearly and comprehensively.
+Participate in code reviews, contributing to a culture of high-quality code and best practices.",2026,Bachelors,0-1,"Python, LLMs, GenAI, MLOps, APIs","Communication, Problem Solving"
+199,AI Developer,Junior,"0 to 1 years of professional experience in AI Agent Developer.
+Proficient in Python and deep learning frameworks like PyTorch and TensorFlow.
+Strong skills in time-series data analysis, feature engineering, and model optimization.
+Familiarity with reinforcement learning algorithms and methodologies.
+Experience with cloud platforms (GCP, AWS, Azure), container technologies (Docker, Kubernetes), and microservices.
+A proven record of deploying ML models and developing autonomous AI agents.
+Knowledge of AI-driven process optimization tools including AI orchestration for enterprise workflows.
+Experience in troubleshooting ML systems
+Adept at proactive problem identification and resolution.
+Certification in MLOps is a plus.",2026,Bachelors,0-1,"Python, Agents, LangChain, LangGraph, TensorFlow/PyTorch, AWS/Azure, ML, MLOps","Communication, Problem Solving"
+190,AI Developer,Junior,"Solid DS & Algo, analytical mindset
+Strong in Python (FastAPI/Flask/Django) or Node.js
+Good knowledge of ReactJS and UI
+Experience with REST APIs and ChatGPT integration
+Strong in database design and queries 
+191,AI Developer,Junior,"Strong analytical and problem-solving skills
+Basic understanding of AI/ML concepts
+Familiarity with Python or JavaScript
+Understanding of APIs and backend systems
+Preferred Qualifications
+Background in Computer Science, Engineering, or Mathematics
+Exposure to AI tools (LangChain, OpenAI APIs)
+Participation in projects, hackathons, or internships
+193,AI Developer,Junior,"Bachelor s degree in Computer Science, IT, or related field
+0 3 years of experience (Freshers with strong fundamentals can apply)
+Strong understanding of software testing concepts (SDLC, STLC, defect lifecycle)
+Good analytical and problem-solving skills
+Ability to understand business logic and workflows quickly
+Strong verbal and written communication skills
+Basic understanding of:
+Manual testing techniques
+API testing concepts
+Databases (SQL basics)
+Familiarity with tools like JIRA or similar bug tracking tools
+Good to Have (Not Mandatory)
+Exposure to automation tools (Selenium or similar)
+Basic programming knowledge ( Java / JavaScript / HTML / CSS )
+Experience or understanding of Agile/Scrum
+Awareness of Git/GitHub
+Understanding of non-functional testing (performance, security basic level)",2026,Bachelors,0-1,"Python, APIs, SQL, Java, Javascript, Git, Github","Communication, Problem Solving"

frontend/data/clean/cleaned_job_descriptions_senior.csv

@@ -0,0 +1,971 @@
+id,role,type,job_desc,year,qualification,experience,tech_skills,soft_skills
+4,AI Engineer,Senior,"6+ years full-stack software engineering experience building scalable web applications, services, and APIs
+Proficiency in JavaScript/TypeScript and/or Python, and comfort working across the stack including frontend development (React or similar frameworks)
+Experience building backend systems, working with various datastores such as (Postgres/pgvector, Pinecone, Redis) and designing APIs.
+Demonstrated curiosity and hands-on experience with AI tools and applications - using modern AI models, agentic IDEs, or building AI-enabled workflows or prototypes.
+Experience building or experimenting with custom developed agentic systems, workflow orchestration tools (n8n), or Agentic browser automation
+A high degree of ownership and initiative, with the ability to operate independently in ambiguous problem spaces
+Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
+Experience collaborating cross-functionally and building trust with stakeholders at all levels of the organization
+Direct experience integrating automated AI Evaluation/Testing/Observability suites to continuously test model effectiveness leveraging platforms such as DeepEval, Langfuse/LangSmith or similar 
+",2026,Not Specified,5-10,"Python, Javascript, React, Full Stack, SQL, APIs, ML, TesnorFlow/PyTorch, n8n","Communication, Problem Solving"
+7,AI Engineer,Senior,"5-10 years overall experience
+3+ years of hands-on Power BI enterprise delivery
+2+ years of SAP BusinessObjects migration experience (or equivalent BI migration)
+SAP BusinessObjects: Universes (UNV/UNX), WebI, contexts, prompts, joins, aggregate awareness
+Power BI / Fabric: Data modeling, DAX, calculation groups, Tabular Editor, Power BI Service governance
+AI & Automation: Azure OpenAI / LLMs, prompt engineering, metadata and document parsing
+Strong SQL and data engineering fundamentals.",2026,Not Specified,5-10,"Python, SQL, PowerBI, SAP, LLMs, Prompt Engineering, Data Engineering","Communication, Problem Solving"
+11,AI Engineer,Senior,"4–6 years of experience in Data Science / Machine Learning / AI Engineering
+Strong programming skills in Python
+Hands-on experience with ML libraries such as Scikit-learn, Pandas, NumPy
+Experience in building ML models (classification, regression, NLP, etc.)
+Practical exposure to Generative AI / LLMs
+Prompt engineering
+RAG (Retrieval-Augmented Generation)
+Chatbot or document-based AI solutions
+Familiarity with frameworks like LangChain, LlamaIndex, or similar
+Experience in building and consuming APIs
+Strong problem-solving and analytical skills
+Experience with cloud platforms (AWS / Azure / GCP)
+Exposure to model deployment tools (Docker, MLflow, etc.)
+Understanding of vector databases (FAISS, Pinecone, etc.)
+Experience working in agile development environments",2026,Not Specified,5-10,"Python, Scikit-Learn, Pandas, NumPy, ML, LLMs, Prompt Engineering, RAG, LangChain, APIs, AWS/Azure, Docker, MLflow, VectorDB","Communication, Problem Solving"
+12,AI Engineer,Senior,"Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related fields.
+2–5 years of hands-on experience in AI/ML or Generative AI development.
+Experience building and deploying production-grade AI solutions.
+Strong programming skills in Python.
+Understanding of Artificial Intelligence and Machine Learning concepts.
+Familiarity with APIs and software development fundamentals.
+Strong analytical and problem-solving abilities.
+Excellent communication and collaboration skills.
+Experience with Generative AI platforms such as OpenAI, Gemini, Claude, or Hugging Face.
+Knowledge of LangChain, LangGraph, CrewAI, AutoGen, or AI Agent frameworks.
+Understanding of RAG architectures and Vector Databases (FAISS, ChromaDB, Pinecone, Weaviate, etc.).
+Knowledge of SQL and database management.
+Familiarity with cloud platforms such as AWS, Azure, or GCP.
+Experience with Git, Docker, and CI/CD pipelines.
+",2026,Bachelors/Masters,1-5,"Python, ML, APIs, GenAI, LangChain, LangGraph, CrewAI, AutoGen, RAG, VectorDB, SQL, Docker, Git, CI/CD, AWS/Azure","Communication, Problem Solving, Analytical Skills"
+15,AI Engineer,Senior,"4–6 years of experience in Data Science / Machine Learning / AI Engineering
+Strong programming skills in Python
+Hands-on experience with ML libraries such as Scikit-learn, Pandas, NumPy
+Experience in building ML models (classification, regression, NLP, etc.)
+Practical exposure to Generative AI / LLMs
+Prompt engineering
+RAG (Retrieval-Augmented Generation)
+Chatbot or document-based AI solutions
+Familiarity with frameworks like LangChain, LlamaIndex, or similar
+Experience in building and consuming APIs
+Strong problem-solving and analytical skills
+Experience with cloud platforms (AWS / Azure / GCP)
+Exposure to model deployment tools (Docker, MLflow, etc.)
+Understanding of vector databases (FAISS, Pinecone, etc.)
+Experience working in agile development environments
+",2026,Not Specified,5-10,"Python, ML, Pandas, NumPy, Scikit-Learn, GenAI, LLMs, Prompt Engineering, RAG,  LangChain, APIs, AWS/Azure, Docker, MLflow, VectorDB","Communication, Problem Solving"
+20,AI Engineer,Senior,"Proven track record with at least 5 years of experience in a technical role focused on AI/ML.
+Expertise in AI/ML frameworks, NLP, and Transformer technologies.
+Strong experience with AWS cloud services, particularly for data processing and machine learning.
+Proficiency in MLOps practices and familiarity with LLMOps.
+Experience with FastAPI or similar frameworks for API development.
+Knowledge of container orchestration with AWS EKS and Bedrock.
+Team handling experience and architecture design experience.
+Proficiency in creating and delivering Powerpoint presentations.
+Knowledge of Responsible AI practices and Nvidia MLOps platform.
+Experience with fine-tuning open-source AI/ML models.
+Familiarity with DevOps practices, including continuous integration, deployment, and monitoring of AI models",2026,Not Specified,1-5,"Python, ML, NLP, MLOps, Feature Engineering, AWS/Azure, APIs","Communication, Problem Solving"
+21,AI Engineer,Senior,"5+ years overall experience in software development, data science, or machine learning.
+1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.
+Strong programming skills in Python and basics in SQL.
+Expertise with LLM/SLM APIs, embeddings, and RAG systems.
+Experience deploying on Google Cloud Platform (GCP) with Vertex AI, and IBM WatsonX.
+Familiarity with agentic AI protocols and exposure to Agent Development Kits (ADKs).
+Experience implementing Model Context Protocol (MCP) for agent coordination.
+Prior exposure to LangGraph, AutoGen, or related orchestration frameworks.
+1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.
+Good communication, stakeholder management and good aptitude, attitude to be flexible.
+Experience in the functional side of Identity and Access management especially on identity governance, access management, privileged access, non-human identities, and worked on any IAM tools like SailPoint, Saviynt, CyberArk and SIEM/SOAR tools like Splunk etc.
+Experience in strategy and roadmap work for Identity and Access management, especially in identifying use cases for automation, agentic AI workflows and roadmap for agentic AI lifecycle
+2 or more years’ experience with developing Robotic Process Automation and/or automation efforts
+2 or more years using Azure OR AWS cloud services
+2 or more years skilled at data visualization (Tableau, PowerBI, etc.)
+2 or more years with modern data engineering with APIs
+2 or more years applying agile SDLC
+Experience in enterprise-scale deployments of AI-driven platforms.
+Contributions to open-source AI/ML projects are a plus.
+",2026,Not Specified,5-10,"Python, APIs, LLMs, Prompt Engineering, LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen,  Anthropic /OpenAI SDKs, MCP, VectorDB, n8n, RAG, Agents, AWS/Azure, PowerBI","Communication, Problem Solving"
+24,AI Developer,Senior,"Core Software Engineering (Required)
+Strong hands-on development in Python / C# / TypeScript/JavaScript (or similar).
+Experience building API-driven services and integrating distributed systems. 
+Strong understanding of non-functional requirements: reliability, availability, scalability, performance, and cost.
+Azure & Platform Engineering
+Hands on experience with Azure AI Foundry for delivering enterprise GenAI solutions in an enterprise context.
+Experience building serverless and asynchronous workloads using Azure Functions (including Durable Functions or equivalent).
+Experience using queues and event driven messaging for decoupled, reliable workflows.
+Experience working with ADLS for data ingestion, storage, and processing.
+Experience using Azure Cognitive Services / Azure AI Services as part of AI solutions.
+Azure Functions + Queues/Eventing (Required)
+Experience with Azure Functions (including Durable Functions or equivalent orchestration patterns).
+Experience implementing asynchronous patterns with queues/eventing for scale and reliability.
+Vector Databases (Required)
+Hands-on experience with vector databases / vector search, including enterprise deployment patterns
+LLM-as-a-Judge Evaluation (Required)
+Experience implementing evaluation approaches that include LLM-as-a-Judge (or equivalent automated evaluation patterns) for quality monitoring and continuous improvement.
+Agent 365 (A365) + Governance Alignment (Required)
+Familiarity/experience working in environments using Agent 365 (A365)-style lifecycle management concepts (e.g., agent registry, governance, monitoring/observability, and access controls)
+Runtime Security / Runtime Protection (Required)
+Experience delivering solutions with runtime protection expectations (runtime security controls, access controls, and monitoring alignment as defined by enterprise governance).
+Experience integrating AI services into enterprise automation platforms (e.g., Power Platform, ServiceNow).
+Familiarity with Azure AI services and data platforms.
+",2026,Not Specified,5-10,"Python, Javascript, AWS/Azure, VectorDB, LLMs, Agent 365","Communication, Problem Solving"
+25,AI Engineer,Senior,"15+ years of overall IT experience
+Strong experience in AI Architecture
+Hands-on experience in Agentic AI
+Strong experience in AI Automation
+Strong programming skills in Python
+Good experience in REST APIs
+Strong knowledge of Azure DevOps
+Hands-on experience in CI/CD
+Experience with GitHub
+Strong solution design and stakeholder management skills
+Experience in enterprise AI transformation initiatives
+Exposure to cloud-based AI services
+Experience in API integration architecture
+Understanding of secure AI solution deployment
+Experience mentoring teams and driving architecture governance
+",2026,Not Specified,15+,"Python, ML, APIs, AWS/Azure, CI/CD, Github, Git, ","Communication, Problem Solving"
+31,AI Developer,Senior,"trong hands-on experience in Python backend development.- Proven expertise with Agentic AI frameworks such as :i. LangGraphii. CrewAIiii. AutoGeniv. LangChain- Experience working with Model Context Protocol (MCP) tools and integrations.- Strong proficiency in FastAPI and modern API development.- Experience with cloud platforms :i. AWS (Bedrock preferred)ii. Microsoft Azure (AI Foundry preferred)- Hands-on experience with :i. Dockerii. Kubernetesiii. CI/CD pipelinesiv. Cloud security and governancePreferred Skills :- Experience with Retrieval-Augmented Generation (RAG) architectures.- Knowledge of vector databases and semantic search solutions.- Familiarity with observability, monitoring, and AI model evaluation frameworks.- Understanding of enterprise AI governance, security, and compliance requirements.Education :- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.- Any Graduate with relevant experience is welcome to apply. ",2026,Bachelors,5-10,"Python, LangChain, LangGraph, CrewAI, AutoGen, MCP, APIs, AWS/Azure, Docker, Kubernetes, CI/CD, RAG, VectorDB","Communication, Problem Solving"
+32,AI Developer,Senior,"To qualify for the role you must have B.E/ B.Tech/ MCA/ MS /M.Tech or equivalent degree in Computer Science discipline. Minimum 4 – 8 years of experience in IT industry with at least 2+ years of experience in AI. Proven track record of working in AI projects from inception to successful deployment. Strong programming skills, preferably in Python, and experience with machine learning frameworks. Exposure / Experience in cloud services like Azure for deploying machine learning models and leveraging cloud-based machine learning services. Familiarity with relational databases like SQL Server / My SQL / PostgreSQL. Familiarity with Docker, Kubernetes, or similar tools for containerization and orchestration of machine learning applications. Knowledge / Experience in AI frameworks and technologies, such as GANs, transformers, and reinforcement learning. Hands-on experience in developing Generative AI solutions using Large Language models preferably Azure OpenAI. Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment. Strong communication skills to effectively collaborate with team members and stakeholders. ",2026,Masters,5-10,"Python,  ML, AWS/Azure, SQL, Docker, Kubernetes, LLMs","Communication, Problem Solving"
+33,AI Developer,Senior,"• 3–6 years of software development experience, with solid hands-on experience in AI/ML or LLM application development.
+• Strong proficiency in Python.
+• Practical experience building APIs and backend services using FastAPI or a similar backend framework.
+• Experience working with PostgreSQLor similar SQL/relational databases.
+• Hands-on experience integrating LLMs into real applications.
+• Goodunderstanding of prompt engineering, structured outputs, and retrieval-based workflows.
+• Understanding of core AI/MLand data science concepts, including training data, model evaluation, embeddings, classification, and basic fine-tuning concepts.
+• Exposure to model training or training support workflows, including data preparation and evaluation.
+• Familiarity with backend integration patterns involving APIs, databases, async processing, and service-to-service communication.
+• Ability to debug issues across prompts, model behavior, application logic, and data flow.
+• Strong problem-solving skills and ability to work independently on implementation tasks.
+• Experience with production use of OpenAI or comparable LLM platforms.
+• Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
+• Experience with agent-style workflows, orchestration patterns, multi-step pipelines, or tool-calling systems.
+• Awareness of recentAI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
+• Experience with batch jobs, background workers, schedulers, or queue-based processing.
+• Familiarity with Docker and containerized deployments.
+• Exposure to AWSor similar cloud platforms.
+• Understanding ofAI observability, token usage, and cost-aware implementation.
+• Experience contributing to technical design and solution planning ",2026,Not Specified,5-10,"Python, APIs, SQL, LLMs, Prompt Engineering, RAG,  MCP, VectorDB, Docker,  AWS/Azure","Communication, Problem Solving"
+34,AI Engineer,Senior,"- Experience in publishing research or contributing to open source AI initiatives
+- Designing AI systems for regulated or enterprise environments
+- Understanding of AI governance, responsible AI practices, and compliance frameworks
+- Experience mentoring technical teams or leading research initiatives
+
+In addition to your technical skills and qualifications, you are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of your day-to-day responsibilities. This includes consistent use of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise, leveraging AI tools to enhance coding, documentation, data analysis, and decision-making workflows, and staying current with evolving AI capabilities and features to improve delivery quality and velocity. 
+",2026,Masters,5-10,"Python, GenAI, LLMs","Communication, Problem Solving"
+42,AI Engineer,Senior,"Python · JS/TS · Neo4j/Cypher · MongoDB · PostgreSQL · FastAPI · LLM APIs · Vector databases · LoRA/PEFT · Docker · Linux CLI
+What we value Side projects nobody asked you to build. Open-source contributions. Intellectual curiosity and ownership over any specific framework pedigree. 
+AWS or GCP working knowledge
+Annotation pipeline or ML dataset preparation experience",2026,Not Specified,1-5,"Python, Javascript, SQL, LLMs, APIs, VectorDB, ML, AWS/Azure","Communication, Problem Solving"
+44,AI Engineer,Senior,"You will focus on creating reusable agent architectures, integrating enterprise APIs, and implementing observability for production AI systems. This is a leadership-focused role that requires deep expertise in Python and modern LLM orchestration techniques. Must have: 5+ years of experience; Deep experience with LangGraph, CrewAI, or AutoGen; Advanced prompt engineering and function calling; Expert-level Python; Experience designing stateful, scalable AI systems; Ability to lead AI initiatives from zero to production. Required tools: langgraph, crewai, autogen, python, llm, prompt engineering, mops. ",2026,Not Specified,5-10,"Python, ML, APIs, LLMs, LangChain, LangGraph, CrewAI, AutoGen, Prompt Engineering, MLOps","Communication, Problem Solving"
+45,AI Engineer,Senior," Strong experience in Artificial Intelligence, Machine Learning (ML), and Generative AI (GenAI)
+• Hands-on with LLMs, RAG pipelines, NLP
+• Experience with LangGraph / AI workflow orchestration
+• Proficiency in Python, FastAPI, API development
+• Strong knowledge of SQL and NoSQL databases
+• Experience in system design and scalable architecture
+• Experience with vector databases (Pinecone, FAISS, Weaviate)
+• Knowledge of cloud platforms (AWS, Azure, GCP)
+• Exposure to MLOps and AI deployment pipelines
+Bachelor’s degree in Computer Science, Engineering, or related field (Any Graduate with relevant experience is welcome)",2026,Bachelors,5-10,"Python, ML, GenAI, LLMs, RAG, NLP, LangChain, LangGraph, APIs, SQL, System Design, VectorDB, MLOps, CI/CD, AWS/Azure","Communication, Problem Solving"
+52,AI Engineer,Senior,"Pytho n as the primary language for data science and ML development (Pandas, NumPy, Scikit-learn
+Familiarity with
+SQ L for data querying and manipulation across modern data warehouses (e.g., BigQuery, Snowflake, PostgreSQL
+(Nice to have) Working knowledge of deep learning frameworks such as
+PyTorc h or
+TensorFlo w for model experimentatio n
+LLM & Generative AI Tooling
+Hands-on experience working with
+large language model API s, including providers such as OpenAI, Anthropic, or Google
+Strong command of
+prompt engineering technique s, including few-shot prompting, chain-of-thought reasoning, and structured output design
+Experience with
+open-source LLM s (e.g., Mistral, LLaMA) and an understanding of when to apply open vs. proprietary models
+Agentic Orchestration & RAG
+Practical experience building
+RAG (Retrieval-Augmented Generation) pipeline s, including chunking strategies, embedding models, and retrieval tuning
+Familiarity with
+agentic orchestration framework s such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGe
+Experience integrating
+vector database s (e.g., pgvector, Pinecone, Weaviate, ChromaDB) into search and retrieval workflow
+Understanding of
+tool/function callin g patterns for LLM-driven automation
+Evaluation & Experimentatio
+Ability to define and implement
+""good enough"" metric s and evaluation frameworks for POC validation
+Experience with
+LLM evaluation librarie s such as RAGAS, TruLens, or DeepEva
+Familiarity with
+experiment tracking tool s such as MLflow or Weights & Biases
+Comfort with
+cost and latency profilin g of LLM-based systems to inform feasibility decisions
+Data & Infrastructure
+Comfortable working within
+cloud environment s (AWS, GCP, or Azure) for data access, compute, and API integration
+Ability to integrate with
+REST API s and third-party data sources during prototyping
+Proficiency with standard development tools:
+Gi t, Jupyter notebooks, VS Code ",2026,Bachelors,5-10,"Python, SQL, TensorFlow/PyTorch, ML, Pandas, NumPy, Scikit-Learn, LLMs, GenAI, APIs, OpenAI, RAG, LangChain, LangGraph, CrewAI, or AutoGen, VectorDB, Prompt Engineering, MLflow, Git, Github, AWS/Azure","Communication, Problem Solving, Analytical Skills"
+53,AI Engineer,Senior,"Must Have Skills/Project Experience/Certifications:
+• 3 - 6 years of hands-on experience of consulting/ industry experience
+• Python: 4+ years with FastAPI, asyncio, data processing libraries
+• AI/ML: Experience with LLMs, prompt engineering, fine-tuning, RAG systems
+• CrewAI: Knowledge of multi-agent frameworks, agent orchestration patterns
+• APIs: Integration with Anthropic, OpenAI, Google AI services
+• Database: Vector databases, PostgreSQL, data modeling for AI workloads
+• Cloud: Experience with cloud-based AI services and deployment
+Good to Have Skills/Project Experience/Certifications:
+• Experience with Langchain, LlamaIndex, or similar frameworks is highly encouraged
+Education:
+• BE/B.Tech/M.C.A./M.Sc (CS) degree or equivalent from accredited university ",2026,Bachelors/Masters,1-5,"Python, APIs, LLMs, Prompt Engineering, RAG, ML, CrewAI, VectorDB, SQL, LangChain, LangGraph","Communication, Problem Solving"
+54,AI Engineer,Senior,"AI Agent Engineering
+LangGraph or equivalent graph-based agent frameworks.
+Multi-step reasoning pipelines.
+Tool usage and orchestration.
+State management and conversational workflows.
+RAG & Vector Search
+End-to-end RAG pipeline design and implementation.
+Experience with vector databases such as:
+Pinecone
+Qdrant
+pgvector
+Weaviate
+Chunking strategies and retrieval optimization.
+Retrieval evaluation methodologies.
+LLM Integration
+OpenAI, Gemini, and Anthropic SDKs.
+Prompt engineering and prompt optimization.
+Structured JSON outputs.
+Context window management.
+Multi-provider LLM integrations.
+Python Backend Development
+Python 3.12
+FastAPI
+Async Python
+Pydantic
+SQLite
+PostgreSQL
+Redis
+Pytest
+Full-Stack Development
+React
+Next.js
+TypeScript
+Modern frontend architecture
+API integration and state management
+ML Engineering Fundamentals
+Evaluation pipelines
+Golden datasets and test suites
+Regression tracking
+Model performance monitoring
+Good to Have
+GIS & Mapping
+ArcGIS REST APIs
+GeoJSON
+MapLibre GL JS
+Spatial queries
+(Strong advantage for initial project assignments.)
+Data Visualization
+Recharts
+D3.js
+Equivalent charting libraries
+Cloud & DevOps
+Docker
+Azure
+AWS
+CI/CD pipelines
+OIDC Authentication
+Product Thinking
+Ability to understand and interpret Figma designs.
+Evaluate trade-offs between engineering effort and business value.
+Deliver solutions aligned with business objectives.
+Technologies You'll Work With
+LayerTechnology Stack
+Agent Frameworks
+LangGraph, LangChain
+LLM Providers
+Gemini, OpenAI, Anthropic
+Backend
+Python 3.12, FastAPI, SQLite, Redis
+Frontend
+Next.js 15, React 19, TypeScript, Zustand
+Data & Visualization
+Recharts, GeoJSON, MapLibre GL JS
+Infrastructure
+Docker, Azure Pipelines, Azure AD ",2026,Not Specified,1-5,"Python, ML, LangChain, LangGraph, RAG, VectorDB, LLMs, APIs, Prompt Engineering, SQL, React, Javascript, Docker, CI/CD, AWS/Azure","Communication, Problem Solving"
+56,AI Engineer,Senior,"Lead the full lifecycle of Generative AI solutions from design and development to deployment encompassing LLM-powered workflows, RAG pipelines, OCR, and Agentic AI systems.
+Architect and implement secure, scalable AI infrastructures using GCP, AWS, or Azure.
+Apply LLMOps best practices, including fine-tuning, advanced prompt engineering, and model optimization, to maximize performance and contextual accuracy.
+Design and maintain APIs and microservices (FastAPI, REST, Spring Boot) to integrate AI capabilities into enterprise systems.
+Build and optimize data pipelines and manage vector databases and Elasticsearch for efficient knowledge retrieval and decision-making.
+Implement MLOps, CI/CD, and DevOps pipelines using Kubernetes, Docker, Jenkins, and Ansible for automated deployment and monitoring.
+Ensure system reliability and observability through logging, monitoring, and infrastructure-as-code practices (e.g., ELK stack).
+Collaborate cross-functionally with product, engineering, and business teams to align AI solutions with organizational goals.
+Mentor and guide junior engineers, setting best practices for scalable, maintainable AI development.
+Required Experience:
+2+ years of professional software engineering experience focused on Generative AI / LLMbased applications. 
+",2026,Not Specified,1-5,"Python, LLMs, MLOps, APIs, AWS/Azure, VectorDB, CI/CD, Docker, Kubernetes, GenAI","Communication, Problem Solving"
+60,AI Engineer,Senior,"Experience in AI/GenAI solution for prompt engineering, architecture, consulting, and enterprise architecture
+Experience in software development
+Excellent communication skills (customer facing position)
+A deep understanding of GenAI/ML technologies and their implementations
+Experience in the financial, healthcare, or insurance industries is a plus
+Bachelor's/Master's degree in Computer Science/data science or related field
+Demonstrated expertise in statistical analysis and machine learning concepts, with proficiency in Python
+Solid understanding and experience in designing, implementing, and optimizing end-to-end machine learning pipelines.
+Minimum 2+ years of experience in Generative AI and Minimum 2+ years in traditional Machine Learning, with a focus on the creation, training, and deployment of services such as recommendation engines, deep learning, and generative AI models.
+1. LLM (GPT); prompt engineering for reflex, model and self-learning agents
+2. Facility with Python to code wrappers, interface with APIs, develop utilities
+3. Experience with packages such as LangChain and LangGraph
+4. Experience with assembling intelligent AI agents to implement variety of use cases
+5. A recent use case for Agentic AI powered by LLMs: NLQ to SQL translator
+6. You MUST have the ability to think through clearly for a solution design,
+Experienced in Large Language Models, Transformers, CNN, TensorFlow, Scikit-learn, Pytorch, NLP libraries, Embedding Models, Vector Databases
+Hands-on experience with OpenAI, Llama/Llama2 and other open-source models, and Azure OpenAI models Education- Engineering, Math and Statistics foundation, (Data Science/Computer Science preferred)",2026,Bachelors/Masters,1-5,"Python, ML, GenAI, APIs, LLMs, Prompt Engineering, LangChain, LangGraph, SQL, TensorFlow/Pytorch, Scikit-Learn, NLP, OpenAI, VectorDB","Communication, Problem Solving"
+61,AI Engineer,Senior,"Artificial Intelligence & Machine Learning
+• Machine Learning
+• Deep Learning
+• Generative AI
+• Reinforcement Learning
+• Neural Networks
+• Predictive Analytics
+Large Language Models (LLMs)
+• OpenAI GPT Models
+• Claude AI
+• Google Gemini
+• Llama Models
+• Mistral AI
+• LangChain
+• LangGraph
+• CrewAI
+• AutoGen
+Programming Languages
+• Python (Expert)
+• JavaScript / TypeScript
+• C#
+• Java
+• SQL
+AI Frameworks & Libraries
+• TensorFlow
+• PyTorch
+• Scikit-Learn
+• Hugging Face Transformers
+• OpenCV
+• Keras
+Backend Development
+• FastAPI
+• Django
+• Flask
+• Node.js
+• REST APIs
+• GraphQL
+Frontend Development
+• React.js
+• Next.js
+• Angular
+• Vue.js
+Mobile Development
+• Flutter
+• React Native
+• Native Android
+• Native iOS
+Desktop Development
+• Electron.js
+• .NET Desktop Applications
+• Python Desktop Applications
+• Cross-platform Desktop Solutions
+Cloud & DevOps
+• AWS
+• Azure
+• Google Cloud Platform
+• Docker
+• Kubernetes
+• CI/CD Pipelines
+Databases
+• PostgreSQL
+• MySQL
+• MongoDB
+• Redis
+• Vector Databases (Pinecone, Weaviate, ChromaDB)
+Preferred Qualifications
+• Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Data Science, or related field.
+• Experience building AI products at scale.
+• Strong portfolio of deployed AI solutions.
+• Experience with enterprise SaaS platforms.
+• Knowledge of AI governance and responsible AI practices.
+• Experience managing technical teams and AI projects ",2026,Bachelors/Masters,5-10,"Python, ML, GenAI, OpenAI, LangChain, LangGraph, CrewAI, AutoGen, Javascript, Java, C#, SQL, TensorFlow/PyTorch, Scikit-Learn, Hugging Face, APIs, Django, React, Docker, Kubernetes, CI/CD, AWS/Azure, VectorDB","Communication, Problem Solving, Analytical Skills"
+64,AI Developer,Senior,"• Strong experience in enterprise backend application development.
+• Good experience designing and building microservices-based applications.
+• Hands-on experience with Java / Spring Boot, Python / FastAPI, Node.js, .NET, or
+similar backend frameworks.
+• Strong understanding of REST APIs, service contracts, JSON, authentication,
+authorization, and integration patterns.
+• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or
+Oracle.
+• Experience with cloud platforms such as AWS, Azure, or GCP.
+• Experience with Docker and container-based application deployment.
+• Understanding of event-driven architecture using SQS, Kafka, RabbitMQ,
+EventBridge, Step Functions, or similar tools.
+• Good understanding of logging, monitoring, error handling, retry logic, performance
+tuning, and production support.
+• Strong problem-solving ability and comfort working on complex enterprise
+workflows.
+AI / LLM Skills Preferred
+• Exposure to LLM-based application development using OpenAI, Azure OpenAI, AWS
+Bedrock, Anthropic, Llama, or similar platforms.
+• Understanding of prompt engineering, structured outputs, confidence scoring, and
+response validation.
+• Experience with RAG, embeddings, vector search, semantic search, or knowledge
+retrieval.
+• Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI,
+AutoGen, or similar frameworks is useful but not mandatory.
+• Ability to work with AI engineers / data scientists to integrate models, prompts,
+retrieval pipelines, and recommendation logic into enterprise applications. ",2026,Not Specified,5-10,"Python, .NET, APIs, Java, SQL, AWS/Azure, ML, LLMs, OpenAI, Prompt Engineering, RAG, VectorDB,  LangChain, LangGraph, CrewAI, AutoGen","Communication, Problem Solving, Analytical Skills"
+66,AI Engineer,Senior,"• Building production AI/LLM applications (not just prototypes)
+• Working with LLMs, APIs, and tool integrations
+• Designing multi-step workflows or pipelines
+• Writing clean, scalable backend systems (Python/Go/Node)
+• Debugging and improving system reliability and performance
+• Understanding of how systems fail and how to handle edge cases
+• Agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
+• Workflow orchestration concepts (RAGs, pipelines, schedulers)
+• Experience with event-driven systems (Kafka, queues, async processing)
+• Basic understanding of:
+• retries / idempotency
+• observability / logging
+• distributed systems",2026,Bachelors,5-10,"Python, LLMs, ML, LangGraph, LangChain, AutoGen, CrewAI, RAG, ","Communication, Problem Solving"
+67,AI Engineer,Senior,"• 2+ years hands-on AI/ML experience
+• Strong Python + PyTorch
+• Experience fine-tuning LLMs (PEFT / LoRA / quantization)
+• Experience with RAG + vector databases
+• Hands-on with diffusion pipelines (Stable Diffusion preferred)
+• Production mindset monitoring, versioning, cost optimization
+• Comfortable in a fast-paced startup environment
+• Experience with AI companion or conversational AI products
+• Experience with ComfyUI workflows
+• GPU infra optimization experience
+• Real-time streaming generation systems ",2026,Bachelors,1-5,"Python, Tensorflow/Pytorch, LLMs, RAG, VectorDB","Communication, Problem Solving"
+69,AI Developer,Senior,"6+ years of hands-on experience in AI/ML solution architecture and delivery
+Proven experience implementing AI/ML use cases for customer-facing platforms
+Strong background in analytics, predictive modeling, and operational intelligence initiatives
+Experience designing scalable AI solutions that drive business outcomes and enhance customer engagement
+Expertise in Machine Learning, Deep Learning, and enterprise AI architectures
+Strong stakeholder management and technical leadership capabilities",2026,Not Specified,15+,"Python, ML, LLMs","Communication, Problem Solving"
+70,AI Engineer,Senior,"• 3+ years of overall IT experience with significant exposure to AI/ML architecture.
+• Strong expertise in Python programming.
+• Hands-on experience with Generative AI (GenAI) technologies and Large Language Models (LLMs).
+• Experience designing and implementing Agentic AI solutions.
+• Strong knowledge of the Databricks Platform .
+• Proficiency in SQL and handling complex data structures.
+• Good understanding of JSON structures , APIs, and system integrations.
+• Proven experience in technical architecture , solution design, and enterprise application integration.
+• Strong problem-solving, communication, and stakeholder management skills. ",2026,Not Specified,1-5,"Python, ML, GenAI, LLMs, Agents, SQL, APIs, ","Communication, Problem Solving"
+72,AI Engineer,Senior,"• Prior 5–9 years of experience in data science, ML engineering, or AI development, with 2+ years focused on Generative AI.
+• Strong hands-on experience with LLMs, transformers, embeddings, and vector databases.
+• Proficiency in Python and GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face).
+• Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning).
+• Experience designing multi‑agent systems, including orchestration, coordination, and distributed reasoning.
+• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
+• Familiarity with 3D deep learning and large scale point cloud processing is a plus.
+• Experience working in fast paced startup environment (preferred).
+• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field. ",2026,Bachelors/Masters,5-10,"Python, GenAI, LangChain, LangGraph, MLOps, CI/CD","Communication, Problem Solving"
+73,AI Engineer,Senior,"pytestSeleniumPostman
+Languages
+Python
+Testing focus
+API TestingUI Testing
+Also listed
+Ai testingLlm testingRag evaluationPrompt engineeringDeepevalPromptfooLangsmithRagasData quality testingGreat expectationsDbtMachine learning lifecycleAutomation testingCi/cd ",2026,Not Specified,5-10,"Python, Pytest, APIs, LLMs, RAG, Prompt Engineering, ML, LangChain, LangGraph, CI/CD","Communication, Problem Solving"
+74,AI Developer,Senior,"• Bachelor’s degree in computer science, Engineering, Data Science, or related technical field
+• Master's degree preferred (Computer Science, AI/ML, or MBA with technical focus)
+• 6+ years of software development experience with 2+ years focused on AI agent development
+• 2+ years of hands-on experience with Azure AI Foundry or similar agent development platforms
+• Proven experience building and deploying production AI agents and automated workflows
+• Microsoft Azure AI Foundry: Deep expertise in Azure AI services ecosystem
+• Agent Development: Multi-agent systems (MOE), reasoning frameworks, and orchestration
+• Workflow Design: Prompt flow, automation pipelines, and human-in-the-loop systems
+• Post-Training Techniques: Fine-tuning, instruction tuning, RLHF, and domain adaptation
+• Model Evaluation: Performance metrics, benchmark development, and A/B testing frameworks
+• Consulting mindset with a strong bias for action.
+• Adept at connecting strategy to execution and simplifying complexity.
+• Passion for enabling people and driving business transformation through AI. ",2026,Bachelors/Masters,5-10,"Python, AWS/Azure, Agents, LLMs, ML","Communication, Problem Solving"
+78,AI Engineer,Senior,"• e4–10 years of software engineering with substantial experience building distributed systems, infra, or ML platforms
+• .Deep practical experience integrating and deploying LLMs in production (RAG, retrieval, embeddings pipelines)
+• .Hands-on experience with agent orchestration frameworks (LangGraph / LangChain or custom agent runtimes) and stateful workflow design
+• .Proven track record building observability, cost controls, and policy enforcement for production services
+.Preferred / differentiator
+• sExperience building or contributing to open-source LLM orchestration tools (LangGraph, LangChain, or similar)
+• .Familiarity with enterprise constraints: on-prem/cloud hybrid deployments, data residency, compliance requirements
+• .Background in security, privacy, or model governance for LLMs
+• .Demonstrated leadership in cross-functional projects and direct customer engagement ",2026,Not Specified,5-10,"Python, ML, LLMs, RAG, LangChain, LangGraph ","Communication, Problem Solving"
+79,AI Engineer,Senior,"Qualifications Bachelor’s/Master’s Degree or equivalent. 8+ years in software/ML engineering, 1.5+ years hands-on with LLMs/GenAI and agentic frameworks. Proven track record shipping production AI systems on at least one hyperscaler (Azure/AWS/GCP). Experience leading 3–6 engineers and owning end-to-end delivery. Required Skills Strong Python experience to build multiple AI-ML/ GenAI Solutions. Should have experience working on Agent orchestration with leading frameworks like LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen . Strong experience working on Vector DB like Pinecone, Milvus, Redis/pgvector); Should have experience working on hybrid search and re-rankers Should have experience on evaluation & observability Experience working on SQL Query , NLP, CV, Deep Learning Algorithms Should have working experience with Open Source Models Experience on UI/UX will be added advantage. #GenAINTT RESUME SELECTION Guidelines: Delivered at least 2 GenAI/Agentic AI solutions for clients Extensive experience of minimum 6+ years on Python Led 2–3 successful client  ",2026,Bachelors/Masters,5-10,"Python, ML, LLMs, GenAI, AWS/Azure, LangChain, LangGraph, CrewAI, AutoGen, VectorDB, RAG, SQL, NLP","Communication, Problem Solving, Analytical Skills"
+80,AI Engineer,Senior,"• Building and deploying autonomous agents
+• LangChain framework for developing applications
+• Retrieval Augmented Generation (RAG) systems
+• Large Language Models (LLMs) and their APIs
+• Solid understanding of safety principles and best practices
+• Resolving hallucinations in the outcomes
+Mandatory Skill sets:
+• Advanced Python programming with expertise in async programming and API developmenT
+• Experience with vector databases and embedding models
+• Proficiency in implementing RAG pipelines and knowledge retrieval systems
+• Familiarity with prompt engineering and LLM optimization techniques
+• Experience with development frameworks and tools
+• Knowledge of modern software development practices (Git, CI/CD, testing)
+Preferred Skill sets:
+• Multiple LLM providers (OpenAI, Anthropic, etc.)
+• Tools for agent orchestration and workflow management
+• Natural Language Processing (NLP) techniques
+• Container technologies (Docker, Kubernetes)
+• Understanding of semantic search and information retrieval concepts
+• Knowledge of agent alignment and safety considerations
+Years of experience required :
+1+yrs to 3+yrs
+Education qualification -Full Time :
+BE/Btech/MCA/Mtech/MBA ",2026,Bachelors/Masters,1-5,"Python, LLMs, ML, LangGraph, LangChain, RAG, APIs, OpenAI, NLP, VectorDB, Git, Github, CI/CD, Docker, Kubernetes","Communication, Problem Solving"
+81,AI Engineer,Senior,"Software Requirements
+• In-depth expertise in Generative AI and Agentic AI technologies
+• Programming proficiency in Python, with experience in frameworks such as PyTorch, TensorFlow, or similar for AI model development
+• Familiarity with cloud AI services like AWS SageMaker, Azure Machine Learning, or GCP AI platform
+• Understanding of APIs and integrations for deploying AI models effectively
+• Experience with data management tools and version control systems like Git
+• Knowledge of blockchain and IoT as they relate to AI deployment
+• Experience using automation and orchestration tools in AI workflows 
+• Programming Languages: Python (required), R, Java (preferred)
+• AI Frameworks & Libraries: PyTorch, TensorFlow, GPT/Transformers, OpenAI API, Hugging Face (required)
+• Data Management: Data preprocessing, management, and model training data pipelines
+• Cloud Technologies: AWS, Azure, GCP (preferred)
+• Model Deployment & APIs: REST API development, containerization with Docker, orchestration with Kubernetes
+• Tools & Methodologies: Agile, CI/CD pipelines, Git version control, model versioning tools
+• Security & Ethics: Data privacy, AI fairness, and compliance considerations
+Experience Requirements
+• At least 5-7 years of experience in software development and leading technology projects
+• Proven track record of delivering AI solutions that enhance business operations
+• Experience mentoring engineering teams in AI project execution
+• Industry experience in banking, finance, or enterprise environments preferred
+• Alternative experience: extensive innovation in AI, natural language processing, or digital transformation initiatives ",2026,Bachelors/Masters,5-10,"Python, GenAI, TensorFlow/Pytorch, AWS/Azure, MCP, ML, APIs, Git, Github, Python, Java, Docker, Kubernetes, CI/CD, NLP","Communication, Problem Solving, Analytical Skills"
+82,AI Engineer,Senior,"• Strong academic record — B.Tech / B.E. / M.Tech / MCA in Computer Science or a related field from a reputable institution (or equivalent).
+• 2–3 years in software / integration engineering, with hands-on third-party API and systems-integration work.
+• Strong data structures, algorithms, and problem-solving skills.
+• Hands-on MCP experience (building or integrating MCP servers/clients) is a strong plus; otherwise solid API-integration depth with eagerness to ramp on MCP.
+Preferred Certifications
+• OAuth 2.0 / OpenID Connect or relevant identity/security certification
+• Any recognised cloud certification (Azure / AWS / GCP) is a plus
+Soft Skills & Cultural Fit
+• Security-first instinct — assumes external services are hostile until proven otherwise.
+• Strong analytical and debugging skills across system boundaries (auth, networking, schema mismatches).
+• Clear written communication — produces precise integration docs and runbooks.
+• Collaborative; comfortable engaging both internal engineers and external vendor teams. ",2026,Bachelors/Masters,1-5,"Python, MCP, APIs, AWS/Azure, ML","Communication, Problem Solving, Analytical Skills"
+83,AI Engineer,Senior,"• Minimum of 4 years of experience as a software engineer
+• Professional experience integrating LLMs into a software product (experience building a chatbot or using simple coding assistants is not sufficient)
+• Experience shipping a production system where a self-improving agent drove the iteration on the system itself (e.g., designed its own tools, refined its own reward function, etc.)
+• Experience curating evaluation or regression sets driving self-improving systems and defining measurable success criteria
+• Experience with modern agent-orchestration tooling (e.g., LangChain, LangGraph)",2026,Not Specified,1-5,"Python, LLMs, LangChain, LangGraph, Agents, APIs, ","Communication, Problem Solving"
+85,AI Engineer,Senior,"Senior AI/ML Engineer – GenAI, LLM, Data Science &
+MLOps
+Experience: 6–7 Years
+Location: On-site
+Employment Type: Full-time
+Notice Period: Immediate Joiners, 15 Days to 1 Month Preferred
+About the Role
+We are looking for a highly skilled Senior AI/ML Engineer to lead the design, development,
+deployment, and optimization of scalable AI solutions. 
+86,AI Engineer,Senior,"- Significant experience in design (architecture, design patterns, reliability, and scaling) and implementation or enhancement of new and current systems
+- Significant experience in system engineering involving analytical systems design and implementation
+- Fluency and specialization with modern languages such as Java, C# or Python
+- Experience in building products using microservices architectural patterns and extensible REST APIs
+- Familiarity with continuous delivery and infrastructure as code
+- Proven experience in cloud, DevOps, or AI modernization initiatives
+- Strong understanding of LLMs, automation, and engineering toolchains
+- Ability to translate AI innovation into business and productivity impact ",2026,Not Specified,1-5,"Python, System Design, Java, C#, AIPs, MLOps, LLMs","Communication, Problem Solving"
+87,AI Engineer,Senior,"• Minimum four years of experience building, training, and deploying machine learning models with measurable real-world impact
+• Deep proficiency in Python and frameworks such as PyTorch or JAX; expertise in model design and optimization
+• Proven experience fine-tuning and deploying large pre-trained and foundation models including language and scientific models
+• Strong understanding of model evaluation including benchmarking, cross-validation, and performance across data distributions
+• Experience with distributed training and large-scale computing environments for high-performance model training
+• Hands-on expertise optimizing models and pipelines for latency, throughput, cost, and production performance
+• Experience with MLOps practices including experiment tracking, model versioning, reproducibility, and cloud deployment
+• Strong problem-solving, collaboration, and communication skills with ability to drive engineering excellence in complex environments ",2026,Not Specified,5-10,"Python, ML, TensorFlow/Pytorch, LLMs, MLOps","Communication, Problem Solving"
+88,AI Engineer,Senior,"Minimum four years of experience building, training, and deploying machine learning models with measurable real-world impact Deep proficiency in Python and frameworks such as PyTorch or JAX; expertise in model design and optimization Proven experience fine-tuning and deploying large pre-trained and foundation models including language and scientific models Strong understanding of model evaluation including benchmarking, cross-validation, and performance across data distributions Experience with distributed training and large-scale computing environments for high-performance model training Hands-on expertise optimizing models and pipelines for latency, throughput, cost, and production performance Experience with MLOps practices including experiment tracking, model versioning, reproducibility, and cloud deployment Strong problem-solving, collaboration, and communication skills with ability to drive engineering excellence in complex environments ",2026,Not Specified,5-10,"Python, ML, Git, Github, MLOps, TensorFlow/PyTorch","Communication, Problem Solving"
+90,AI Engineer,Senior,"• • 6-12 years of software engineering experience, with at least 2 years focused on AI/ML application development.
+• • Hands-on experience shipping LLM-powered applications to real users or stakeholders: RAG pipelines, prompt engineering at system level, agentic workflows.
+• • Production-level proficiency in Python and/or TypeScript for rapid prototyping.
+• • Experience with cloud AI platforms—AWS Bedrock strongly preferred; SageMaker, Azure AI, or Anthropic Claude acceptable.
+• • Working experience with agentic AI frameworks: LangChain, LangGraph, CrewAI, AWS Strands Agents, Claude Managed Agents, AWS Agentcore, or equivalent.
+• • Strong API integration skills: REST, webhooks, MCP or similar agent-to-service patterns.
+• • Demonstrated ability to facilitate business discovery sessions and present demos to technical & non-technical stakeholders.
+• • Experience pairing with distributed teams to develop production-grade agentic AI systems.
+• • Primary interface with Lead AI Solutions Architects and business stakeholders.
+• • Requires strong English communication, executive presence, and async documentation discipline.
+• • Bachelor’s degree in computer science, Software Engineering, AI/ML, or related field.
+• • Agile/Scrum experience.
+• • Builds RAG pipelines, API integrations, agentic workflow components, and prompt systems.
+• • Writes transition documentation, contributes to Confluence knowledge base.
+• • Must demonstrate strong async communication, self-direction, and clean handoff discipline.
+Required Experience
+• • Has shipped at least one highly performant and reliable production grade LLM-powered agentic AI application to real users or business stakeholders (not just Kaggle or personal projects).
+• • Can write production-quality Python or TypeScript.
+• • Can explain what RAG is, what agentic workflows are, and when you would (and would not) use each.
+• • Has worked with at least one cloud AI platform (AWS Bedrock preferred).
+• • Comfortable with ambiguity — can define scope from an unstructured problem statement.
+Preferred
+• • Experience with AI evaluation frameworks, prompt testing, and LLM output quality assurance.
+• • Background in digital marketing technology, SaaS platforms, or sales/marketing operations.
+• • Familiarity with AI Development Lifecycle (AI-DLC) methodologies.
+• • Experience with Agent-to-Agent(A2A) integration. ",2026,Not Specified,5-10,"Python, ML, RAG, VectorDB, APIs, LLMs, AWS/Azure, MCP, Agents, LangChain, LangGraph, Prompt Engineering","Communication, Problem Solving, Analytical Skills"
+91,AI Engineer,Senior,"Responsibilities: Design and implement autonomous agents using LangChain / Crew.ai / SK / Autogen and other relevant frameworks Develop and optimize RAG systems for improved information retrieval and response generation Create robust evaluation frameworks for testing agent performance and safety Implement monitoring and logging systems for agent behavior Develop documentation and best practices for agent development Contribute to the improvement of agent architecture and capabilities Hands-on experience with: Building and deploying autonomous agents LangChain framework for developing applications Retrieval Augmented Generation (RAG) systems Large Language Models (LLMs) and their APIs Solid understanding of safety principles and best practices Resolving hallucinations in the outcomes Mandatory Skill sets: Advanced Python programming with expertise in async programming and API developmenT Experience with vector databases and embedding models Proficiency in implementing RAG pipelines and knowledge retrieval systems Familiarity with prompt engineering and LLM optimization techniques Experience with development frameworks and tools Knowledge of modern software development practices (Git, CI/CD, testing) Preferred Skill sets: Multiple LLM providers (OpenAI, Anthropic, etc.) Tools for agent orchestration and workflow management Natural Language Processing (NLP) techniques Container technologies (Docker, Kubernetes) Understanding of semantic search and information retrieval concepts Knowledge of agent alignment and safety considerations Years of experience required: 2 to 3+yrs Education qualification: Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related fields ",2026,Bachelors,1-5,"Python, ML, RAG, VectorDB, APIs, LLMs, AWS/Azure, MCP, Agents, LangChain, LangGraph, Prompt Engineering, Git, Github, CI/CD, AutoGen, CrewAI, GenAI, NLP, Docker, Kubernetes","Commuication, Problem Solving"
+92,AI Engineer,Senior,"3+ years of overall IT experience with significant exposure to AI/ML architecture.
+Solid expertise in Python programming.
+Hands-on experience with Generative AI (GenAI) technologies and Large Language Models (LLMs).
+Experience designing and implementing Agentic AI solutions.
+Strong knowledge of the Databricks Platform.
+Proficiency in SQL and handling complex data structures.
+Good understanding of JSON structures, APIs, and system integrations.
+Proven experience in technical architecture, solution design, and enterprise application integration.
+Strong problem-solving, communication, and stakeholder management skills. ",2026,Not Specified,1-5,"Python, ML, GenAI, Agents, LangChain, LangGraph, LlamaIndex, SQL, APIs, System Design, LLMs","Communication, Problem Solving"
+93,AI Engineer,Senior,"Key Skills:
+• Python
+• Machine Learning & Deep Learning
+• TensorFlow / PyTorch
+• NLP, Computer Vision, Generative AI
+• AWS / Azure / GCP
+• MLOps & Model Deployment
+• APIs & Microservices
+Responsibilities:
+• Lead AI/ML projects from development to deployment.
+• Build and optimize machine learning models and pipelines.
+• Collaborate with business and technical teams to deliver AI solutions.
+• Mentor and guide AI/ML engineers.
+• Ensure best practices in model development and deployment.
+• Stay updated with the latest AI and Generative AI technologies.
+Requirements:
+• 8–10 years of overall experience with strong expertise in AI/ML.
+• Hands-on experience in Python and AI frameworks.
+• Experience with cloud platforms and model deployment. 
+95,AI Engineer,Senior,"• Experience with Large Language Models (LLMs) and Generative AI application development.
+• Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
+• Strong understanding of RAG, embeddings, vector search, and semantic retrieval techniques.
+• Proficiency in Python and API integration.
+• Experience integrating enterprise data sources and external tools into AI workflows.
+• Familiarity with cloud-native platforms and data engineering environments.
+• Ability to design scalable, modular, and production-ready AI architectures.
+Preferred Skills
+• Experience with vector databases such as Pinecone, Chroma, Weaviate, or pgvector.
+• Exposure to MLOps, AI monitoring, and observability tools.
+• Experience in enterprise software delivery or client-facing environments.
+• Knowledge of modern web frameworks for AI-enabled applications.
+Preferred Qualifications
+• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
+• Strong analytical, problem-solving, and communication skills.
+• Ability to work independently and collaboratively in a fast-paced environment. ",2026,Bachelors,1-5,"Python, LLMs, GenAI, ML, LangChain, LangGraph, CrewAI, AutoGen, APIs, VectorDB, System Design, MLOps, ","Communication, Problem Solving, Analytical Skills"
+96,AI Engineer,Senior,"You will be responsible for setting up scalable cloud environments, building seamless CI/CD pipelines, and establishing cutting-edge deployment frameworks for Large Language Models (LLMs) and foundational AI applications.Key Responsibilities1. GenAI & LLMOps InfrastructureDesign and manage cloud infrastructure tailored for hosting, fine-tuning, and serving Generative AI models.Implement and manage infrastructure for AI orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel).Optimize vector databases (e.g., Pinecone, Milvus, Qdrant, or pgvector in PostgreSQL) for highly efficient Retrieval-Augmented Generation (RAG) pipelines.Implement cost-optimization strategies for heavy compute resources (GPUs/TPUs).2. Core DevOps & Cloud EngineeringArchitect, scale, and maintain secure, cloud-native infrastructure utilizing AWS, Azure, or GCP.Orchestrate and manage containerized workloads using Docker and Kubernetes.Implement robust Infrastructure as Code (IaC) using Terraform, OpenTofu, or CloudFormation.Build, maintain, and optimize secure CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) for automated software and model deployment.3. Monitoring, Observability & SecuritySet up advanced observability tools (Prometheus, Grafana, Datadog) to track both infrastructure health and AI model performance metrics (latency, token usage, drift).Collaborate with engineering teams to ensure highly secured IT solutions, embedding data privacy, vulnerability scanning, and guardrails for LLM prompts/outputs.Required Technical Skills & QualificationsExperience: 5+ years of total experience in DevOps/Cloud Engineering, with at least 1–2 years actively supporting AI/ML or GenAI workloads in production.AI/LLM Ecosystem: Practical exposure to deploying LLMs (OpenAI APIs, Hugging Face, Anthropic, or open-source models like Llama via Ollama/vLLM).Containerization & Orchestration: Deep expertise in Kubernetes (EKS, AKS, or GKE) and Docker.Infrastructure as Code: Proven mastery of Terraform.Databases: Familiarity with traditional databases (PostgreSQL, MongoDB) as well as vector stores.Programming: Strong scripting and automation skills in Python (highly preferred for AI workflows), Go (Golang), or Bash. ",2026,Not Specified,5-10,"Python, LLMs, CI/CD, MLOps, LangChain, LlamaIndex, RAG, VectorDB, SQL,  Docker, Kubernetes, AWS/Azure, Github, Git, OpenAI, APIs, Hugging Face","Communication, Problem Solving"
+97,AI Engineer,Senior,"• 5+ years of experience in AI/ML engineering with strong software development fundamentals.
+• Strong programming skills in Python; knowledge of SQL and Java is an advantage.
+• Hands-on experience in Machine Learning, Deep Learning, and Natural Language Processing (NLP).
+• Experience building Generative AI applications using Large Language Models (LLMs).
+• Strong expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, and Agentic AI.
+• Hands-on experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, and OpenAI SDK.
+• Experience working with vector databases such as Pinecone, FAISS, ChromaDB, Milvus, or Weaviate.
+• Proficiency in ML frameworks and libraries including PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas, and NumPy.
+• Experience developing and deploying REST APIs using FastAPI or Flask.
+• Good understanding of MLOps, including MLflow, Kubeflow, model deployment, monitoring, model versioning, and CI/CD pipelines.
+• Experience with Docker, Kubernetes, Git, GitHub Actions, or Jenkins.
+• Hands-on experience with at least one cloud platform: AWS, Azure, or GCP, including AI services such as SageMaker, Azure OpenAI, AWS Bedrock, or Vertex AI.
+• Experience working with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis.
+• Knowledge of software engineering best practices, scalable system design, and Agile development methodologies.
+• Excellent analytical, problem-solving, communication, and stakeholder management skills.
+• Ability to work collaboratively in cross-functional teams and deliver production-grade AI solutions. ",2026,Not Specified,5-10,"Python, Java, SQL, NLP, GenAI, LLMs, RAG, Prompt Engineering, Agents, LangChain, LangGraph, LlamaIndex, Hugging Face, OpenAI, APIs, VectorDB, Pandas, Numpy, Scikit-Learn, TensorFlow/PyTorch, MLflow, MLOps, CI/CD, Git, Github, Docker, Kubernetes, AWS/Azure, System Design","Communication, Problem Solving"
+98,AI Engineer,Senior,"• 8–10 years of software engineering experience.
+• Strong hands-on experience with LangChain and LangGraph (Mandatory).
+• Strong knowledge of Agentic AI and Large Language Models (LLMs).
+• Proficiency in Python.
+• Experience with RAG architectures, vector databases, embeddings, and prompt engineering.
+• Experience integrating AI models through APIs and AI orchestration frameworks.
+• Strong understanding of software design principles and scalable application architecture.
+• Excellent analytical and problem-solving skills. ",2026,Not Specified,5-10,"Python, ML, LLMs, Agents, LangChain, LangGraph, RAG, VectorDB, System Design, Prompt Engineering","Communication, Problem Solving, Analytical Skills"
+99,AI Engineer,Senior,"AI & Machine Learning
+• Strong expertise in Machine Learning, Deep Learning, and Data Science.
+• Hands-on experience with Generative AI and Large Language Models (LLMs).
+• Experience with Prompt Engineering, Fine-Tuning, and Model Evaluation.
+• Strong understanding of NLP, embeddings, vector search, and semantic retrieval.
+Frameworks & Tools
+• Python programming expertise.
+• Experience with TensorFlow, PyTorch, Scikit-learn, LangChain, LlamaIndex, or
+similar frameworks.
+• Experience working with OpenAI, Anthropic, Gemini, Claude, Llama, Mistral, or
+equivalent models.
+RAG & Vector Databases
+• Experience building production-grade RAG systems.
+• Hands-on experience with vector databases such as Pinecone, Weaviate,
+ChromaDB, Milvus, or FAISS.
+• Knowledge of embedding models and retrieval strategies.
+MLOps & Deployment
+• Strong experience with MLOps practices and model lifecycle management.
+• Experience with Docker, Kubernetes, CI/CD pipelines, and model monitoring.
+• Expertise in deploying AI/ML solutions in production environments.
+Cloud & Infrastructure
+• Experience with AWS, Azure, or Google Cloud Platform (GCP).
+• Understanding of scalable cloud-native architectures.
+• Experience with REST APIs, microservices, and distributed systems.
+Preferred Qualifications
+• Experience leading AI/ML projects and mentoring engineering teams.
+• Knowledge of AI governance, model security, and responsible AI practices.
+• Exposure to multi-agent systems and autonomous AI workflows.
+• Contributions to open-source AI projects or published research are a plus.
+Educational Qualification
+• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data
+Science, Machine Learning, or a related field. ",2026,Bachelors/Masters,5-10,"Python, ML, GenAI, LLMs, Prompt Engineering, NLP, VectorDb, RAG, TensorFlow/PyTorch, Scikit-Learn, Agents, LangChain, LangGraph, LlamaIndex, APIs, MLOps, CI/CD, Docker, Kubernetes, Git, Github, AWS/Azure, OpenAI","Communication, Problem Solving"
+100,AI Engineer,Senior,"Success in this role requires:
+• Mentoring and helping others to grow as engineers and developers
+• Have excellent written and verbal communication skills
+• Ability to excel in a distributed, remote team environment
+• Self-drive to work on key initiatives
+• Take pleasure in making things happen and listen to the input from peers
+• Data-driven decision-making skills
+• Embracing a best-idea-wins approach, regardless of the source
+• Collaboration with cross-functional teams to define, design, and ship new features
+• Staying current with emerging trends and technologies in AI and cloud computing
+We are looking for:
+• 10+ years of experience in building large-scale cloud-based distributed applications
+• Strong experience in building multi-tenant SaaS applications
+• Expertise with AI technologies, including LLM models, RAG, LangChain, and LlamaIndex
+• Ability to design and develop scalable and robust AI-driven applications
+• Excellent problem-solving, debugging, and analytical skills with great attention to detail
+• Experience with microservices and cloud-based architectures/design patterns
+• Demonstrated proficiency in English at the C1 level
+Technical Skills:
+• Extensive experience in Python and Java
+• Proficient with NLP libraries and tools (spaCy, NLTK, Hugging Face Transformers)
+• Skilled in model deployment frameworks (TensorFlow Serving, MLflow, Kubernetes-based deployments)
+• Hands on Experience with ETL processes, data pipelines, and data warehousing solutions
+• Expertise with top-tier datastores (MongoDB, AWS DocumentDB, SQL Server, MySQL)
+• Proficient in Linux
+• Experience with Apache Tomcat, Nginx, AWS, Docker, and Kubernetes
+• Familiarity with CI/CD pipelines and tools (Jenkins, GitLab CI, CircleCI)
+• Understanding of container orchestration tools and concepts
+• Knowledge of security best practices in cloud and distributed applications
+• Experience with infrastructure as code (IaC) tools (Terraform, CloudFormation). ",2026,Not Specified,15+,"Python, LLMs, RAG, Agents, LangChain, LangGraph, LlamaIndex, NLP, TensorFlow/PyTorch, ML, Github, Git, AWS/Azure, CI/CD, SQL, MLflow, MLOps, Docker, Kubernetes","Communication, Problem Solving, Analytical Skills"
+103,AI Engineer,Senior,"• 7–12 years of overall software/AI engineering experience
+• Strong hands‑on experience with AWS Bedrock in real projects (not PoC-only exposure)
+• Proven experience building agentic AI or tool‑using LLM workflows
+• Solid experience with Python for GenAI development
+• Hands‑on experience with RAG architectures , embeddings, and vector stores
+• Strong AWS fundamentals: IAM, networking basics, serverless services
+• Clear understanding of GenAI risks, hallucination management, prompt controls
+Good‑to‑Have Skills
+• Experience with frameworks like LangChain, LlamaIndex, Semantic Kernel
+• Exposure to enterprise domains such as BFSI, healthcare, insurance, or pharma
+• Experience in model evaluation, benchmarking, and observability
+• Prior experience working on customer-facing or production AI platforms
+Mandatory Skills:
+• Hands‑on AWS Bedrock implementation (real project experience, not learning/demo)
+• Agentic AI / LLM agents / tool‑calling workflows
+• RAG architectures + vector databases
+• Strong Python background ",2026,Not Specified,5-10,"Python, AWS/Azure, LLMs, GenAI, RAG, VectorDB, LangChain, LangGraph, LlamaIndex, Agents","Communication, Problem Solving"
+104,AI Engineer,Senior,"• 4+ yrs building AI-powered products served in production.
+• Strong Python; production LLM/RAG; embeddings + vector databases (HNSW/IVF indexing).
+• Inference serving (FastAPI/Triton/TorchServe-class); latency/throughput optimization.
+• NLP fundamentals; API design; caching and queueing.
+Strong signals
+• Learning-to-rank / recommendation systems; multilingual/low-resource NLP; semantic search; on-device inference integration; prompt/reasoning orchestration. ",2026,Not Specified,1-5,"Python, LLMs, VectorDB, RAG, APIs, NLP","Communication, Problem Solving"
+105,AI Engineer,Senior,"-5+ years of professional experience as a Fullstack Developer building production applications
+-Strong hands‑on experience with Microsoft Azure (App Services, Azure Functions, APIs, storage, authentication, etc.)
+-Solid backend development experience (e.g., .NET, Java, Node.js, or Python) with API and service‑oriented architectures
+-Frontend development experience with modern frameworks (React, Angular, or similar)
+-Experience working on cloud‑based or AI‑adjacent products, including integration with AI/ML services or data‑driven platforms ",2026,Not Specified,5-10,"Python, .NET, Java, Javascript, React, APIs, AWS/Azure, ML","Communication, Problem Solving"
+106,AI Engineer,Senior,"• 9–12 years of overall experience with strong ML engineering focus
+• Hands-on experience in ML and DL frameworks (TensorFlow / PyTorch / scikit-learn)
+• Experience working with LLMs and GenAI architectures
+• Strong Python programming skills
+• Experience deploying models on AWS (SageMaker, EC2, Lambda, S3)
+• Experience building REST APIs for model serving
+• Strong understanding of data preprocessing and feature engineering ",2026,Not Specified,5-10,"Python. ML, TensorFlow/PyTorch, Scikit-Learn, LLMs, GenAI, AWS/Azure, APIs","Communication, Problem Solving"
+111,AI Engineer,Senior,"• 5+ years of experience in Python-based application development.
+• Hands-on experience building enterprise AI applications using LangGraph and LangChain.
+• Experience integrating LLMs through AWS Bedrock.
+• Strong knowledge of PostgreSQL and Snowflake.
+• Experience designing scalable cloud-native applications on AWS.
+• Excellent problem-solving and communication skills.
+• Experience working in Agile/Scrum environments. ",2026,Not Specified,5-10,"Python, ML, LLMs, AWS/Azure, SQL, APIs, Agents, LangGraph, LangChain","Communication, Problem Solving"
+167,AI Developer,Senior,"Required Skills & Qualifications :Technical Skills :- Strong hands-on experience in Python backend development.- Proven expertise with Agentic AI frameworks such as :i. LangGraphii. CrewAIiii. AutoGeniv. LangChain- Experience working with Model Context Protocol (MCP) tools and integrations.- Strong proficiency in FastAPI and modern API development.- Experience with cloud platforms :i. AWS (Bedrock preferred)ii. Microsoft Azure (AI Foundry preferred)- Hands-on experience with :i. Dockerii. Kubernetesiii. CI/CD pipelinesiv. Cloud security and governancePreferred Skills :- Experience with Retrieval-Augmented Generation (RAG) architectures.- Knowledge of vector databases and semantic search solutions.- Familiarity with observability, monitoring, and AI model evaluation frameworks.- Understanding of enterprise AI governance, security, and compliance requirements.Education :- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.- Any Graduate with relevant experience is welcome to apply. ",2026,Bachelors,5-10,"Python, Agents, LangChain, LangGraph, LlamaIndex, LLMs, ML, Pandas, RAG, MCP, APIs, AutoGen, CrewAI, Docker, Kubernetes, AWS/Azure, CI/CD, VectorDB","Communication, Problem Solving, Analytical Skills"
+168,AI Developer,Senior,"Required Qualifications
+• 3–6 years of software development experience, with solid hands-on experience in AI/ML or LLM application development.
+• Strong proficiency in Python.
+• Practical experience building APIs and backend services using FastAPI or a similar backend framework.
+• Experience working with PostgreSQLor similar SQL/relational databases.
+• Hands-on experience integrating LLMs into real applications.
+• Goodunderstanding of prompt engineering, structured outputs, and retrieval-based workflows.
+• Understanding of core AI/MLand data science concepts, including training data, model evaluation, embeddings, classification, and basic fine-tuning concepts.
+• Exposure to model training or training support workflows, including data preparation and evaluation.
+• Familiarity with backend integration patterns involving APIs, databases, async processing, and service-to-service communication.
+��� Ability to debug issues across prompts, model behavior, application logic, and data flow.
+• Strong problem-solving skills and ability to work independently on implementation tasks.
+Preferred Qualifications
+• Experience with production use of OpenAI or comparable LLM platforms.
+• Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
+• Experience with agent-style workflows, orchestration patterns, multi-step pipelines, or tool-calling systems.
+• Awareness of recentAI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
+• Experience with batch jobs, background workers, schedulers, or queue-based processing.
+• Familiarity with Docker and containerized deployments.
+• Exposure to AWSor similar cloud platforms.
+• Understanding ofAI observability, token usage, and cost-aware implementation.
+• Experience contributing to technical design and solution planning ",2026,Bachelors/Masters,5-10,"Python, LLMs, ML, APIs, SQL, Prompt Engineering, VectorDB, OpenAI, MCP, Docker, AWS/Azure","Communication, Problem Solving"
+169,AI Developer,Senior,"• Minimum 3 years of Creatio development experience including solution design and architecture on a production enterprise implementation
+• Proficiency in C#, JavaScript and T-SQL, the core Creatio development stack
+• Deep knowledge of Creatio business process designer, data model, section and detail customisation
+• Experience with Creatio REST API and OData integration patterns
+• Creatio Academy certification or demonstrable equivalent knowledge
+AI platform: essential
+• Python proficiency, data structures, API clients, async patterns, file handling
+• Claude Code Must be demonstrated in the technical interview. You will use Claude Code daily to navigate codebases, diagnose issues, design solutions and implement features collaboratively with AI assistance
+• GitHub mandatory. Branching strategy, pull requests, code review, issue tracking and collaborative development workflows.
+• Familiarity with REST API design and OAuth 2.0 authentication flows
+Nice to have
+• Azure DevOps — pipeline configuration, resource management, deployment automation
+• Experience with LLM API integration (Anthropic, OpenAI or equivalent)
+• Plotly Dash or equivalent Python data visualisation framework
+• Google Workspace API integration experience
+• Microsoft 365 / Graph API integration experience 
+170,AI Developer,Senior,"• 3+ years of experience in Generative AI, AI Operations, Prompt Engineering, AI Evaluation, Product Operations, Business Analysis, Technical Writing, Content Strategy, or related fields.
+• Strong understanding of Generative AI, Large Language Models (LLMs), and AI-powered applications.
+• Hands-on experience with AI platforms such as ChatGPT, Claude, and Gemini.
+• Experience creating and optimizing prompts for business or operational use cases.
+• Strong analytical, problem-solving, and critical-thinking abilities.
+• Excellent written and verbal communication skills.
+• Ability to work independently in a remote environment.
+Good to Have
+• Experience with Retrieval-Augmented Generation (RAG) concepts and knowledge-based AI systems.
+• Familiarity with AI agents, workflow automation tools, and no-code/low-code AI platforms.
+• Experience with AI evaluation frameworks and RLHF (Reinforcement Learning from Human Feedback).
+• Basic understanding of APIs, Python, SQL, or automation platforms.
+• Experience working with AI training data, annotations, or model evaluation projects.
+• Knowledge of AI governance, trust & safety, and responsible AI practices. ",2026,Not Specified,1-5,"Python, GenAI, ML, Prompt Engineering, LLMs, RAG, Agents, LangChain, LangGraph, APIs","Communication, Problem Solving"
+171,AI Developer,Senior,"Required Technical SkillsProgramming Language
+• Python
+AI/ML Technologies
+• Machine Learning and Artificial Intelligence
+• Supervised Learning
+• Unsupervised Learning
+• Reinforcement Learning
+Frameworks & Libraries
+• TensorFlow
+• PyTorch
+• Keras
+• Scikit-learn
+• Pandas
+• NumPy
+• Hugging Face
+Deep Learning
+• Neural Networks
+• Convolutional Neural Networks (CNN)
+• Recurrent Neural Networks (RNN)
+Model Training FrameworksAnalytics & Monitoring
+• ELK / Elastic Stack
+Data Engineering
+• Data ETL Tools
+Development & Deployment
+• Software Development Practices
+• Containerization Technologies
+• API Development and Integration
+Experience
+• 6 to 9 years of relevant experience in AI Development, Data Science, Machine Learning, and AI-based application development.
+• Hands-on experience with Python and leading AI/ML frameworks.
+• Experience in model training, evaluation, deployment, and optimization.
+Qualification
+• B.E./B.Tech/M.E./M.Tech/MCA/M.Sc. (Computer Science, Data Science, Artificial Intelligence, Information Technology, Mathematics, Statistics, or equivalent) from a recognized institute/university. ",2026,Bachelors/Masters,5-10,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, Pandas, NumPy, Hugging Face, APIs, Docker","Communication, Problem Solving, Analytical Skills"
+182,AI Developer,Senior,"Required Skills
+• Strong proficiency in Python Programming.
+• Experience with AI/ML libraries such as:
+• NumPy
+• Pandas
+• Scikit-learn
+• TensorFlow
+• PyTorch
+• Knowledge of Generative AI, LLMs, Prompt Engineering, and AI APIs.
+• Experience with Django, Flask, or FastAPI.
+• Strong understanding of databases (MySQL, PostgreSQL, MongoDB).
+• Knowledge of Git and version control systems.
+• Familiarity with cloud platforms is an advantage.
+• Good communication, presentation, and mentoring skills.
+Preferred Qualifications
+• Bachelor's/Master's Degree in Computer Science, IT, Data Science, AI, or related field.
+• Industry experience in AI/ML or Full Stack Development.
+• Previous teaching or training experience is preferred.
+• Relevant certifications in Python, AI, ML, or Data Science are an added advantage. ",2026,Bachelors/Masters,1-5,"Python, ML, NumPy, Pandas, Scikit-Learn, TensorFlow/PyTorch, GenAI, Prompt Engineering, LLMs, APIs, Django, SQL, Git, Github, AWS/Azure","Communication, Problem Solving"
+187,AI Developer,Senior,"Agentic AIRetrieval Augmented GenerationMachine Learning
+Artificial IntelligenceNatural Language ProcessingPython",2026,Bachelors,5-10,"Python, RAG, ML, NLP","Communication, Problem Solving"
+188,AI Developer,Senior,"46 years of experience in machine learning and deep learning.
+Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers.
+Experience with LLMs, GANs, VAEs, or diffusion models.
+Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools.
+Understanding of NLP, computer vision, and multimodal AI systems.
+Experience with model evaluation metrics and A/B testing.
+Excellent problem-solving and communication skills.",2026,Bachelors,5-10,"Python, ML, TensorFlow/PyTorch, Hugging Face, LLMs, AWS/Azure, MLOps, NLP","Communication, Problem Solving"
+189,AI Developer,Senior,"Expertise in Agentic AI, Generative AI development
+Expertise in coding using python from a programming language perspective
+Good work experience of ML models, LLM, Retrieval-Augmented Generation(RAG), Model
+Context Protocol(MCP), Langchain, Langgraph etc.
+Experienced in understanding functional requirement, integrate AI models with microservices/APIs, connect to databases
+Experienced in using CI/CD tools like Github, Jenkins
+Experienced in Agile project using Jira tool",2026,Bachelors,5-10,"Python, GenAI, Agent, LangChain, LangGraph, RAG, LLMs, ML, MCP, CI/CD, Github, Git","Communication, Problem Solving"
+190,AI Developer,Senior,"3-5 years of experience in software development with hands-on experience implementing AI/ML or Generative AI solutions in production environments.
+Strong understanding of AI technologies across the Software Development Lifecycle (SDLC), including AI coding assistants, AI-driven testing frameworks, and automation tools.
+Experience with MLOps concepts, AI model deployment, monitoring, and lifecycle management.
+Proficiency in one or more programming languages such as Python, Java, or .NET.
+Strong knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and modern AI frameworks and tools.
+Demonstrated ability to design and deliver AI Proof of Concepts that showcase technical feasibility and business impact.
+Excellent communication and consulting skills with the ability to translate complex AI concepts into clear business value and ROI.
+Experience working directly with clients and stakeholders to gather requirements, present AI solutions, and influence decision-making.
+Strong analytical, problem-solving, collaboration, and stakeholder management skills.
+Passion for continuous learning and driving AI innovation across engineering teams.",2026,Bachelors,1-5,"Python, ML, GenAI, MLOps, LLMs, Java, .NET, Prompt Engineering, ","Communication, Problem Solving"
+194,AI Developer,Senior,"artificial intelligence
+image processingpythonnatural language processingneural networksnumpymachine learningpandasdeep learningtensorflowrdata sciencepredictive modelingcomputer visionkerasflaskopencvpattern recognition",2026,Bachelors,1-5,"Python, Pandas, NumPy, NLP, ML, TensorFlow/PyTorch","Communication, Problem Solving"
+195,AI Developer,Senior,"Experience
+1 to 4 years of experience in Data Engineering, Data Warehousing, or related roles
+Hands-on experience in data modeling and Data Mart development preferred
+Technical Skills
+Strong expertise in Data Modeling & Data Warehousing concepts
+Programming: Python, SQL, PL/SQL, Shell scripting
+SQL expertise in query optimization and performance tuning
+Data Processing: Apache Spark, ETL/ELT frameworks
+Workflow orchestration: Apache Airflow, DBT
+Cloud Platforms: AWS and Oracle Cloud (OCI)
+Data Platforms: Snowflake, Databricks or similar modern warehouses
+Databases: Oracle, MS SQL, and NoSQL databases
+Streaming Technologies: Kafka / event-driven systems
+API Development: RESTful APIs and integrations
+Containerization: Docker (Kubernetes is a plus)
+Data Architecture: Data Lake, Data Warehouse, Data Mart, Data Vault
+Exposure to AI/ML workflows and GenAI concepts is an added advantage
+Familiarity with DevOps/DataOps (CI/CD, version control, automation)",2026,Bachelors,1-5,"Python, SQL, AWS/Azure, APIs, GenAI, Docker, Kubernetes, CI/CD, Git, Github","Communication, Problem Solving"
+196,AI Developer,Senior,"Degree in CS, AI, ML, or related field.
+Proficient in Python and ML frameworks (TensorFlow, PyTorch).
+Strong in algorithms, data structures, and statistics.
+Experience with data processing and cloud platforms.
+Excellent analytical and communication skills.
+197,AI Developer,Senior,"Junior AI Developer (13 Years)
+12 years of experience in application development or AI-related projects.
+Basic experience with AI models, APIs, or agent frameworks.
+Strong problem-solving skills and eagerness to learn AI systems and deployments.
+Ability to work under guidance and follow defined implementation plans.
+Preferred Skills
+Experience with LLM-based agents or agent orchestration frameworks.
+Knowledge of Python, Node.js, or similar backend technologies.
+Exposure to cloud platforms (AWS, Azure, or GCP).
+Familiarity with Docker, CI/CD pipelines, or scalable deployment models.
+Understanding of security and performance considerations for AI applications.",2026,Bachelors,10-15,"Python, ML, APIs, LLMs, Javascript, AWS/ Azure, CI/CD, Docker","Communication, Problem Solving"
+198,AI Developer,Senior,"Strong proficiency in programming languages such as Python, Java, or C++.
+Experience with AI frameworks like TensorFlow, PyTorch, or Keras.
+Knowledge of ML algorithms and deep learning techniques.
+Familiarity with cloud platforms such as AWS or Google Cloud.
+Excellent problem-solving skills and attention to detail.
+Ability to work collaboratively in a team environment and communicate effectively with stakeholders.",2026,Bachelors,1-5,"Python, Java, C, C++, TensorFlow/PyTorch, ML, AWS/Azure","Communication, Problem Solving"

frontend/data/sample_data/cli.txt

@@ -0,0 +1,117 @@
+ Job Description Provided : 
+ Python as primary language. Microsoft Azure required as the primary cloud platform.     Hands-on experience building with Azure AI Foundry.     Claude Code 
+experience and expertise required, including hands-on development of skills and plugins on the platform.     This is non-negotiable for the role. LangGraph 
+experience required.     Demonstrated ability to design state graphs, conditional edges, and multi-agent compositions.     Model Context Protocol experience 
+required.     Comfortable designing tool calls and building protocol wrappers.     Agentic pair programming with generative AI as the primary working mode.    
+Prior experience is required.     Pydantic for data validation and structured outputs across agent systems and APIs.     SQL proficiency and PostgreSQL 
+experience. Vector database experience (pgvector, Azure AI Search, or similar).     Familiarity with modern data platforms such as Snowflake and Databricks.   
+Multi-step agent systems with proper evaluation and validation.     Strong fluency across modern frontier language models such as the GPT, Claude, and Gemini 
+model families.     Model selection is driven by the requirements of each task and the practical considerations of cost.     The discipline to choose mature, 
+proven frameworks for AI engineering work.     Technical decisions are grounded in clear engineering justification and supported by data.     Docker and 
+containerization for development and deployment workflows.     FastAPI or equivalent web frameworks for building APIs and backend services.     Working 
+knowledge of GitHub workflows, code review discipline, and infrastructure-as-code patterns
+
+ Job Role : 
+ AI Engineer
+
+ Type : 
+ Junior
+
+
+ TOP Skills 
+
+ apis                      0.78  ███████████████████████
+
+ langgraph                 0.78  ███████████████████████
+
+ vectordb                  0.76  ██████████████████████
+
+ mcp                       0.75  ██████████████████████
+
+ langchain                 0.74  ██████████████████████
+
+ rag                       0.72  █████████████████████
+
+ llms                      0.72  █████████████████████
+
+ agents                    0.70  ████████████████████
+
+ crewai                    0.66  ███████████████████
+
+ autogen                   0.64  ███████████████████
+
+ openai                    0.63  ██████████████████
+
+ sql                       0.61  ██████████████████
+
+ n8n                       0.60  ██████████████████
+
+ aws/azure                 0.59  █████████████████
+
+ prompt engineering        0.56  ████████████████
+
+ llamaindex                0.55  ████████████████
+
+ javascript                0.50  ███████████████
+
+ python                    0.50  ███████████████
+
+ docker                    0.48  ██████████████
+
+ github                    0.48  ██████████████
+
+ git                       0.45  █████████████
+
+ genai                     0.41  ████████████
+
+ react                     0.41  ████████████
+
+ ml                        0.32  █████████
+
+ java                      0.24  ███████
+
+ ci/cd                     0.22  ██████
+
+ nlp                       0.16  ████
+
+ django                    0.16  ████
+
+ mlops                     0.15  ████
+
+ system design             0.12  ███
+
+ full stack                0.11  ███
+
+ kubernetes                0.11  ███
+
+ .net                      0.10  ███
+
+ anthropic /openai sdks    0.07  ██
+
+ powerbi                   0.07  █
+
+ tensorflow/pytorch        0.06  █
+
+ c#                        0.05  █
+
+ hugging face              0.05  █
+
+ mlflow                    0.03  
+
+ scikit-learn              0.02  
+
+ pandas                    0.01  
+
+ numpy                     0.01  
+
+ feature engineering       0.01  
+
+ c++                       0.01  
+
+ model evaluation          0.01  
+
+ model training            0.00  
+
+ c                         0.00  
+
+ r                         0.00  

frontend/data/sample_data/eval.txt

@@ -0,0 +1,113 @@
+ Model Evaluation Metrics
+
+label                    support   precision   recall    f1    
+.net                     1         0.00        0.00      0.00
+agents                   14        0.43        0.43      0.43
+anthropic /openai sdks   1         0.00        0.00      0.00
+apis                     21        0.62        0.62      0.62
+autogen                  5         0.50        0.80      0.62
+aws/azure                17        0.78        0.82      0.80
+c#                       1         0.00        0.00      0.00
+ci/cd                    6         0.86        1.00      0.92
+crewai                   5         0.44        0.80      0.57
+django                   2         0.00        0.00      0.00
+docker                   6         0.44        0.67      0.53
+genai                    16        0.44        0.69      0.54
+git                      7         0.43        0.86      0.57
+github                   7         0.40        0.86      0.55
+hugging face             1         0.17        1.00      0.29
+java                     3         0.12        0.33      0.18
+javascript               5         0.44        0.80      0.57
+kubernetes               4         0.60        0.75      0.67
+langchain                19        0.75        0.63      0.69
+langgraph                16        0.73        0.69      0.71
+llamaindex               5         0.38        0.60      0.46
+llms                     30        0.85        0.57      0.68
+mcp                      3         0.30        1.00      0.46
+ml                       31        0.86        0.61      0.72
+mlflow                   1         1.00        1.00      1.00
+mlops                    6         0.29        0.83      0.43
+n8n                      3         0.40        0.67      0.50
+nlp                      6         0.26        0.83      0.40
+numpy                    6         0.67        0.33      0.44
+openai                   6         0.23        0.50      0.32
+pandas                   7         0.67        0.29      0.40
+prompt engineering       9         0.53        0.89      0.67
+python                   40        0.95        1.00      0.98
+rag                      14        0.69        0.79      0.73
+react                    2         0.25        0.50      0.33
+scikit-learn             6         0.50        0.67      0.57
+sql                      11        0.35        0.55      0.43
+system design            4         0.00        0.00      0.00
+tensorflow/pytorch       10        0.59        1.00      0.74
+vectordb                 9         0.50        0.89      0.64
+
+Micro-F1: 0.624 | Macro-F1: 0.420
+
+=== PER-LABEL ACCURACY ===
+label                    accuracy%   support   trap? 
+.net                     97.6        1         Wrong
+agents                   61.9        14        Wrong
+anthropic /openai sdks   97.6        1         Wrong
+apis                     61.9        21        Right
+autogen                  88.1        5         Wrong
+aws/azure                83.3        17        Right
+c                        100.0       0         Wrong
+c#                       97.6        1         Wrong
+c++                      100.0       0         Wrong
+ci/cd                    97.6        6         Right
+crewai                   85.7        5         Wrong
+django                   95.2        2         Wrong
+docker                   83.3        6         Wrong
+feature engineering      100.0       0         Wrong
+full stack               100.0       0         Wrong
+genai                    54.8        16        Wrong
+git                      78.6        7         Wrong
+github                   76.2        7         Wrong
+hugging face             88.1        1         Wrong
+java                     78.6        3         Wrong
+javascript               85.7        5         Wrong
+kubernetes               92.9        4         Right
+langchain                73.8        19        Right
+langgraph                78.6        16        Right
+llamaindex               83.3        5         Wrong
+llms                     61.9        30        Right
+mcp                      83.3        3         Wrong
+ml                       64.3        31        Right
+mlflow                   100.0       1         Right
+mlops                    69.0        6         Wrong
+model evaluation         100.0       0         Wrong
+model training           100.0       0         Wrong
+n8n                      90.5        3         Wrong
+nlp                      64.3        6         Wrong
+numpy                    88.1        6         Right
+openai                   69.0        6         Wrong
+pandas                   85.7        7         Right
+powerbi                  100.0       0         Wrong
+prompt engineering       81.0        9         Right
+python                   95.2        40        Right
+r                        100.0       0         Wrong
+rag                      81.0        14        Right
+react                    90.5        2         Wrong
+scikit-learn             85.7        6         Wrong
+sql                      61.9        11        Wrong
+system design            90.5        4         Wrong
+tensorflow/pytorch       83.3        10        Right
+vectordb                 78.6        9         Wrong
+Right : 
+ 15
+Wrong : 
+ 33
+Total Labels : 
+ 48
+Keyword Accuracy : 31.25%
+
+
+BASELINE: 
+
+Baseline always predicts: ['apis', 'aws/azure', 'genai', 'langchain', 'langgraph', 'llms', 'ml', 'python', 'rag', 'sql', 'tensorflow/pytorch', 'vectordb']
+Baseline Micro-F1: 0.538 | Macro-F1: 0.152
+
+VERDICT 
+
+Model meaningfully beats the naive baseline.

frontend/data/sample_data/test.txt

@@ -0,0 +1,47 @@
+Current Dataset Entries :
+    80 Senior, 80 Junior, 80 Internship : 120 AI Engineer, 120 AI Developer
+    48 Keywords/labels
+
+Goal :
+    None
+    
+Job Description :
+    Python as primary language. Microsoft Azure required as the primary cloud platform. 
+    Hands-on experience building with Azure AI Foundry. 
+    Claude Code experience and expertise required, including hands-on development of skills and plugins on the platform. 
+    This is non-negotiable for the role. LangGraph experience required. 
+    Demonstrated ability to design state graphs, conditional edges, and multi-agent compositions. 
+    Model Context Protocol experience required. 
+    Comfortable designing tool calls and building protocol wrappers. 
+    Agentic pair programming with generative AI as the primary working mode. 
+    Prior experience is required. 
+    Pydantic for data validation and structured outputs across agent systems and APIs. 
+    SQL proficiency and PostgreSQL experience. Vector database experience (pgvector, Azure AI Search, or similar). 
+    Familiarity with modern data platforms such as Snowflake and Databricks. 
+    Multi-step agent systems with proper evaluation and validation. 
+    Strong fluency across modern frontier language models such as the GPT, Claude, and Gemini model families. 
+    Model selection is driven by the requirements of each task and the practical considerations of cost. 
+    The discipline to choose mature, proven frameworks for AI engineering work. 
+    Technical decisions are grounded in clear engineering justification and supported by data. 
+    Docker and containerization for development and deployment workflows. 
+    FastAPI or equivalent web frameworks for building APIs and backend services. 
+    Working knowledge of GitHub workflows, code review discipline, and infrastructure-as-code patterns
+
+    Single Line :
+        Python as primary language. Microsoft Azure required as the primary cloud platform. Hands-on experience building with Azure AI Foundry. Claude Code experience and expertise required, including hands-on development of skills and plugins on the platform. This is non-negotiable for the role. LangGraph experience required. Demonstrated ability to design state graphs, conditional edges, and multi-agent compositions. Model Context Protocol experience required. Comfortable designing tool calls and building protocol wrappers. Agentic pair programming with generative AI as the primary working mode. Prior experience is required. Pydantic for data validation and structured outputs across agent systems and APIs. SQL proficiency and PostgreSQL experience. Vector database experience (pgvector, Azure AI Search, or similar). Familiarity with modern data platforms such as Snowflake and Databricks. Multi-step agent systems with proper evaluation and validation. Strong fluency across modern frontier language models such as the GPT, Claude, and Gemini model families. Model selection is driven by the requirements of each task and the practical considerations of cost. The discipline to choose mature, proven frameworks for AI engineering work. Technical decisions are grounded in clear engineering justification and supported by data. Docker and containerization for development and deployment workflows. FastAPI or equivalent web frameworks for building APIs and backend services. Working knowledge of GitHub workflows, code review discipline, and infrastructure-as-code patterns
+    
+Role : 
+    AI Engineer
+
+Type : 
+    Junior
+
+Keys to be predicted (15):
+    Python, LLMs, LangGraph, MCP, GenAI, VectorDB, SQL, APIs, Docker, Agents, Github, CI/CD, Git, AWS/Azure, Prompt Engineering
+
+Keys with less score (< 0.3):
+    CI/CD
+    (1/15)
+
+Accuracy (recall):
+    (14/15) * 100 = 93.34%

model/MODEL.md

@@ -0,0 +1,233 @@
+# JobAnalyze 6k v1.0 Skill Classifier
+
+A lightweight **multi-label** PyTorch model that predicts a fixed set of **skills/keywords** from a job description plus a provided **role** and **job type**.
+
+This README documents the exact artifacts and behavior implemented in:
+
+- `model/model.py` (training definition)
+- `model/pred.py` (inference wrapper)
+- `model/prep/data_prep.py` (feature creation)
+
+Sample runs and evaluation numbers referenced from:
+
+- `data/sample_data/test.txt`
+- `data/sample_data/eval.txt`
+- `data/sample_data/cli.txt`
+
+---
+
+## Model summary
+
+### Task type
+
+- **Multi-label classification** (each skill is predicted independently)
+
+### Inputs
+
+- `job_desc` (job description text)
+- `role` (free text, appended)
+- `job_type` / `type` (free text, appended)
+
+These are concatenated during prediction as:
+
+```text
+{job_desc} {role} {job_type}
+```
+
+### Features
+
+- TF-IDF features created by `model/prep/data_prep.py` using:
+  - `TfidfVectorizer(max_features=150, stop_words='english', ngram_range=(1, 2), min_df=2)`
+- Artifacts:
+  - `model/prep/vectorizer.pkl`
+  - `model/prep/label_vocab.json`
+  - `model/prep/prepared_data.npz`
+
+### Labels
+
+- A fixed vocabulary of skills/keywords stored in `model/prep/label_vocab.json`
+- In training artifacts:
+  - `NUM_LABELS = len(VOCAB)`
+  - In sample data: **48 Keywords/labels**
+
+### Network architecture (the “6k / 6000 parameter” model)
+
+`model/model.py` defines a small feed-forward network:
+
+- Linear(input_dim → hidden_dim=32)
+- ReLU
+- Dropout(p=0.3)
+- Linear(hidden_dim=32 → num_labels)
+
+The file name and training printout refer to the total parameter count computed at runtime.
+
+---
+
+## Training (model/model.py)
+
+**Do not run `model/model.py` directly for day-to-day use.** It is designed to be executed via `pipeline.py` (and/or the notebooks).
+
+Training uses:
+
+- Loss: `torch.nn.BCEWithLogitsLoss(pos_weight=pos_weight)`
+  - `pos_weight` is computed per-label from the training set (class imbalance handling)
+  - Clamped with `max=10.0`
+- Optimizer: `Adam(lr=1e-3, weight_decay=1e-4)`
+- Epochs: `300`
+
+### Outputs (saved artifacts)
+
+At the end of training, the following are written to `model_out/`:
+
+- `model_out/skill_classifier.pt`
+- `model_out/training_history.json`
+
+The test suite asserts these exist (see `test/test_model.py`).
+
+---
+
+## Inference (model/pred.py)
+
+`model/pred.py` exposes a prediction helper:
+
+```python
+JobAnalyze_6k(job_desc, role="", job_type="", top_k=50) -> List[(str, float)]
+```
+
+Key behavior:
+
+- Loads artifacts from repo-relative paths:
+  - `model/prep/label_vocab.json`
+  - `model/prep/vectorizer.pkl`
+  - `model_out/skill_classifier.pt`
+- Vectorizes the concatenated text with TF-IDF and produces logits through the trained network.
+- Converts logits to probabilities with `sigmoid`.
+- Ranks all labels by probability descending and returns the top results.
+
+> Note: `top_k` is capped by the number of labels effectively returned from the ranked list (in the code, slicing is applied directly).
+
+---
+
+## Evaluation snapshot (from data/sample_data)
+
+### Micro/Macro F1
+
+From `data/sample_data/eval.txt`:
+
+- **Micro-F1: 0.624**
+- **Macro-F1: 0.420**
+
+### Baseline comparison
+
+Also from `data/sample_data/eval.txt`, baseline always predicts a fixed set of frequent labels:
+
+- Baseline Micro-F1: **0.538**
+- Baseline Macro-F1: **0.152**
+
+The evaluation script prints:
+
+> “Model meaningfully beats the naive baseline.”
+
+### Per-label and “trap” analysis
+
+The evaluation output includes per-label precision/recall/F1 and an additional heuristic:
+
+- “trap?” flags labels where the model does not perform better than a trivial always-zero expectation (within a small tolerance).
+
+From `data/sample_data/eval.txt`:
+
+- Right: **15**
+- Wrong: **33**
+- Total labels: **48**
+- Keyword Accuracy: **31.25%**
+
+---
+
+## Example: single inference test (data/sample_data/test.txt)
+
+`data/sample_data/test.txt` contains a job description plus:
+
+- Role: **AI Engineer**
+- Type: **Junior**
+
+It lists **15 keys to be predicted**, including:
+
+- Python, LLMs, LangGraph, MCP, GenAI, VectorDB, SQL, APIs, Docker, Agents, Github, CI/CD, Git, AWS/Azure, Prompt Engineering
+
+Reported performance:
+
+- Accuracy (recall): **93.34%** (14/15)
+
+---
+
+## Example: CLI output format (data/sample_data/cli.txt)
+
+`cli/jobauto.py` uses `JobAnalyze_6k` from `model.pred` and prints:
+
+- The job description provided
+- Role and Type
+- A ranked “TOP Skills” list as `{label} {probability}` plus a text bar
+
+From `data/sample_data/cli.txt`, the top-ranked skills include (with example probabilities):
+
+- apis ~0.78
+- langgraph ~0.78
+- vectordb ~0.76
+- mcp ~0.75
+- langchain ~0.74
+- rag ~0.72
+
+---
+
+## Data prep artifacts (model/prep/data_prep.py)
+
+`model/prep/data_prep.py` creates all required inputs for training and inference.
+
+It:
+
+1. Loads cleaned job description dataset
+2. Normalizes and fixes known skill spelling issues (`SKILLS_FIX`)
+3. Applies synonym replacement using `model/prep/sym_map.py`
+4. Builds a multi-hot label vector for the vocabulary
+5. Vectorizes job text with TF-IDF
+6. Splits into train/test and saves:
+   - `prepared_data.npz`
+   - `label_vocab.json`
+   - `vectorizer.pkl`
+
+---
+
+## Reproducibility / how to use
+
+### Requirements (high level)
+
+See `requirements.txt` and `pyproject.toml`.
+
+### Minimum artifacts required for prediction
+
+For `model/pred.py` to work, these must exist:
+
+- `model/prep/label_vocab.json`
+- `model/prep/vectorizer.pkl`
+- `model_out/skill_classifier.pt`
+
+If any are missing, `model/pred.py` raises a `FileNotFoundError` with guidance.
+
+### Recommended workflow
+
+- Run the full pipeline via `pipeline.py` (which coordinates data prep + training).
+- Use `cli/jobauto.py` for interactive predictions.
+
+---
+
+## Notes on “JobAnalyze 6k”
+
+Despite the “6k / 6000 parameter” naming, the true parameter count is computed dynamically in `model/model.py`.
+
+The implementation is intentionally small:
+
+- TF-IDF input features
+- 1 hidden layer with 32 units
+- Multi-label BCE loss with class imbalance reweighting
+
+This design keeps inference fast and model size small while still providing meaningful gains over the naive baseline (see evaluation snapshot above).

model/Model.py

@@ -0,0 +1,122 @@
+""" 
+Model.py - DO NOT RUN THIS SCRIPT!
+
+Run this script, prep/data_prep.py and the notebooks through pipeline.py
+"""
+
+import json
+import torch
+import numpy as np
+import torch.nn as nn
+from torch.utils.data import Dataset, DataLoader
+from pathlib import Path
+
+REPO_ROOT = Path(__file__).resolve().parent.parent
+
+torch.manual_seed(42)
+
+DATA_DIR = Path(__file__).resolve().parent / 'prep'
+
+assert (DATA_DIR / 'prepared_data.npz').exists(), f"Missing {DATA_DIR / 'prepared_data.npz'}"
+assert (DATA_DIR / 'label_vocab.json').exists(), f"Missing {DATA_DIR / 'label_vocab.json'}"
+
+data = np.load(DATA_DIR / 'prepared_data.npz')
+
+X_train = data['X_train']
+X_test = data['X_test']
+y_train = data['y_train']
+y_test = data['y_test']
+
+with open(DATA_DIR / 'label_vocab.json', encoding='utf-8') as f:
+    VOCAB = json.load(f)
+
+    
+DIM = X_train.shape[1]
+NUM_LABELS = len(VOCAB)
+
+class SkillData(Dataset):
+    def __init__(self, X, y) -> torch.tensor:
+        self.X = torch.tensor(X, dtype=torch.float32)
+        self.y = torch.tensor(y, dtype=torch.float32)
+        
+    def __len__(self) -> len:
+        return len(self.X)
+    
+    def __getitem__(self, idx) -> int:
+        return self.X[idx], self.y[idx]
+    
+train_ds = SkillData(X_train, y_train)
+test_ds = SkillData(X_test, y_test)
+
+train_loader = DataLoader(train_ds, batch_size=64, shuffle=True)
+test_loader = DataLoader(test_ds, batch_size=64, shuffle=False)
+
+class SkillClassifier(nn.Module):
+    def __init__(self, input_dim, num_labels, hidden_dim=32, dropout=0.3) -> None:
+        super().__init__()
+        self.net = nn.Sequential(
+            nn.Linear(input_dim, hidden_dim),
+            nn.ReLU(),
+            nn.Dropout(dropout),
+            nn.Linear(hidden_dim, num_labels)       
+        )
+        
+    def forward(self, x) -> float:
+        return self.net(x)
+    
+jobanalyze_6k = SkillClassifier(DIM, NUM_LABELS)
+
+total_params = sum(p.numel() for p in jobanalyze_6k.parameters())
+trainable_params = sum(p.numel() for p in jobanalyze_6k.parameters() if p.requires_grad)
+
+print(f"Total Parameters: {total_params:,}")
+print(f"Trainable Parameters: {trainable_params:,}")
+
+pos_counts = y_train.sum(axis=0)
+neg_counts = len(y_train) - pos_counts
+pos_weight = torch.tensor(neg_counts / (pos_counts + 1e-6), dtype=torch.float32)
+pos_weight = torch.clamp(pos_weight, max=10.0)
+
+criterion = nn.BCEWithLogitsLoss(pos_weight=pos_weight)
+optimizer = torch.optim.Adam(jobanalyze_6k.parameters(), lr=1e-3, weight_decay=1e-4)
+
+EPOCHS = 300
+history = {'train_loss' : [], 'test_loss' : []}
+
+for epoch in range(1, EPOCHS + 1):
+    jobanalyze_6k.train()
+    train_losses = []
+    for xb, yb in train_loader:
+        optimizer.zero_grad()
+        logits = jobanalyze_6k(xb)
+        loss = criterion(logits, yb)
+        loss.backward()
+        optimizer.step()
+        train_losses.append(loss.item())
+        
+    jobanalyze_6k.eval()
+    test_losses = []
+    with torch.no_grad():
+        for xb, yb in test_loader:
+            logits = jobanalyze_6k(xb)
+            loss = criterion(logits, yb)
+            test_losses.append(loss.item())
+            
+    train_loss = sum(train_losses) / len(train_losses)
+    test_loss = sum(test_losses) / len(test_losses)
+    history['train_loss'].append(train_loss)
+    history['test_loss'].append(test_loss)
+    
+    if epoch % 10 == 0 or epoch == 1:
+        print(f"Epoch {epoch:3d} | train_loss {train_loss:.4f} | test_loss {test_loss:.4f}")
+        
+out_dir = REPO_ROOT / 'model_out'
+out_dir.mkdir(parents=True, exist_ok=True)
+
+torch.save(jobanalyze_6k.state_dict(), out_dir / 'skill_classifier.pt')
+with open(out_dir / 'training_history.json', 'w') as f:
+    json.dump(history, f)       
+    
+print("\n Saved Model")
+print(f"Final train_loss : {history['train_loss'][-1]:.4f} | "
+      f"Final test_loss : {history['test_loss'][-1]:.4f}")

model/__init__.py

@@ -0,0 +1,10 @@
+"""Model package.
+
+Exporting SkillClassifier directly from `model.py` triggers training-time
+side effects (loading datasets) at import time, which breaks CLI usage.
+
+CLI code should import from `model.pred` / `model.model` as needed.
+"""
+
+
+

model/eval.py

@@ -0,0 +1,106 @@
+""" 
+eval.py - RUN after pipeline.py
+
+evaluation metrics for the model
+"""
+
+import json
+import numpy as np
+import torch
+from sklearn.metrics import precision_recall_fscore_support, f1_score, accuracy_score
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parent.parent
+
+from Model import SkillClassifier
+
+sys.path.insert(0, '.')
+
+data = np.load('prep/prepared_data.npz')
+
+X_train = data['X_train']
+y_train = data['y_train']
+X_test = data['X_test']
+y_test = data['y_test']
+
+with open('prep/label_vocab.json') as f:
+    VOCAB = json.load(f)
+    
+model = SkillClassifier(X_train.shape[1], len(VOCAB))
+model.load_state_dict(torch.load(ROOT / 'model_out' / 'skill_classifier.pt', map_location='cpu'))
+
+model.eval()
+
+with torch.no_grad():
+    logits = model(torch.tensor(X_test, dtype=torch.float32))
+    probs = torch.sigmoid(logits).numpy()
+    
+THRESHOLD = 0.5
+preds = (probs >= THRESHOLD).astype(int)
+
+precision, recall, f1, support = precision_recall_fscore_support(
+    y_test,
+    preds,
+    average=None,
+    zero_division=0
+)
+micro_f1 = f1_score(y_test, preds, average='micro', zero_division=0)
+macro_f1 = f1_score(y_test, preds, average='macro', zero_division=0)
+
+print("\n Model Evaluation Metrics\n")
+print(f"{'label':25s}{'support':10s}{'precision':12s}{'recall':10s}{'f1':6s}")
+for lbl, p, r, f, s in zip(VOCAB, precision, recall, f1, support):
+    if s > 0:
+        print(f"{lbl:25s}{int(s):<10d}{p:<12.2f}{r:<10.2f}{f:.2f}")
+        
+print(f"\nMicro-F1: {micro_f1:.3f} | Macro-F1: {macro_f1:.3f}")
+
+print("\n=== PER-LABEL ACCURACY ===")
+print(f"{'label':25s}{'accuracy%':12s}{'support':10s}{'trap?':6s}")
+
+is_right = 0
+is_wrong = 0
+
+for i, lbl in enumerate(VOCAB):
+    label_acc = accuracy_score(y_test[:, i], preds[:, i])
+    s = int(support[i])
+    
+    always_zero_acc = 1.0 - (y_test[:, i].sum() / len(y_test))
+    is_trap = always_zero_acc >= label_acc - 0.01
+    
+    trap_flag = "Wrong" if is_trap else "Right"
+    print(f"{lbl:25s}{label_acc*100:<12.1f}{s:<10d}{trap_flag}")
+
+    if trap_flag == 'Right':
+        is_right += 1
+    else:
+        is_wrong += 1
+        
+total_labels = is_right + is_wrong
+
+print("Right : \n", is_right)
+print("Wrong : \n", is_wrong)
+
+print("Total Labels : \n", total_labels)
+
+key_acc = (is_right / total_labels) * 100
+
+print(f"Keyword Accuracy : {round(key_acc, 2)}%\n")
+
+train_freq = y_train.mean(axis=0)
+baseline_preds = np.tile((train_freq >= 0.3).astype(int), (len(y_test), 1))
+
+baseline_micro_f1 = f1_score(y_test, baseline_preds, average='micro', zero_division=0)
+baseline_macro_f1 = f1_score(y_test, baseline_preds, average='macro', zero_division=0)
+
+print(f"\nBASELINE: \n")
+baseline_labels = [lbl for lbl, f in zip(VOCAB, train_freq) if f >= 0.3]
+print(f"Baseline always predicts: {baseline_labels}")
+print(f"Baseline Micro-F1: {baseline_micro_f1:.3f} | Macro-F1: {baseline_macro_f1:.3f}")
+
+print("\nVERDICT \n")
+if micro_f1 > baseline_micro_f1 + 0.05:
+    print("Model meaningfully beats the naive baseline.")
+else:
+    print("Model is roughly tied with (or worse than) just guessing the most")

model/pred.py

@@ -0,0 +1,80 @@
+"""
+pred.py - predictor for evaluation
+"""
+
+import json
+import pickle
+from typing import List, Tuple
+import numpy as np
+import torch
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parent.parent
+
+from torch import nn
+
+class SkillClassifier(nn.Module):
+    def __init__(self, input_dim, num_labels, hidden_dim=32, dropout=0.3):
+        super().__init__()
+        self.net = nn.Sequential(
+            nn.Linear(input_dim, hidden_dim),
+            nn.ReLU(),
+            nn.Dropout(dropout),
+            nn.Linear(hidden_dim, num_labels),
+        )
+
+    def forward(self, x):
+        return self.net(x)
+
+def JobAnalyze_6k(job_desc: str = "", role: str = "", job_type: str = "", top_k: int = 50) -> List[Tuple[str, float]]:
+    """
+    Predict top-k skills.
+    
+    Current top-k = 48
+    """
+    prep_dir = ROOT / "model" / "prep"
+    if not prep_dir.exists():
+        alt = ROOT / "prep"
+        if alt.exists():
+            prep_dir = alt
+
+    label_path = prep_dir / "label_vocab.json"
+    vector_path = prep_dir / "vectorizer.pkl"
+    weights_path = ROOT / "model_out" / "skill_classifier.pt"
+
+    if not label_path.exists():
+        raise FileNotFoundError(
+            f"Missing {label_path}. Make sure you ran data_prep and model training."
+        )
+    if not vector_path.exists():
+        raise FileNotFoundError(
+            f"Missing {vector_path}. Make sure you ran data_prep."
+        )
+    if not weights_path.exists():
+        raise FileNotFoundError(
+            f"Missing {weights_path}. Make sure you ran model/model.py."
+        )
+
+    with open(label_path, encoding="utf-8") as f:
+        label_vocab = json.load(f)
+    with open(vector_path, "rb") as f:
+        vectorizer = pickle.load(f)
+
+    input_dim = int(getattr(vectorizer, "vocabulary_", {}).__len__()) or vectorizer.transform([""]).shape[1]
+
+    model = SkillClassifier(input_dim, len(label_vocab))
+    model.load_state_dict(torch.load(weights_path, map_location="cpu"))
+
+    model.eval()
+    
+    combined_text = f"{job_desc} {role} {job_type}"
+    X = vectorizer.transform([combined_text]).toarray().astype(np.float32)
+    
+    with torch.no_grad():
+        logits = model(torch.tensor(X))
+        probs = torch.sigmoid(logits).numpy()[0]
+        
+    ranked = sorted(zip(label_vocab, probs), key=lambda x: -x[1])
+    return ranked[:top_k]
+    
+        

model/prep/data_prep.py

@@ -0,0 +1,93 @@
+""" 
+data_prep.py - DO NOT RUN THIS SCRIPT!
+
+Run this script, model/model.py and the notebooks through pipeline.py
+"""
+
+import json
+from pathlib import Path
+import numpy as np
+import pandas as pd
+import pickle
+from collections import Counter
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.model_selection import train_test_split
+
+from sym_map import SYNONYM_MAP
+
+df = pd.read_csv(r'C:\Portfolio-Projects\Job-Description-Analysis\data\clean\cleaned_job_descriptions.csv')
+
+SKILLS_FIX = {
+    'tesnorflow/pytorch': 'tensorflow/pytorch',
+    'numpyhugging face':  'numpy',
+    'sytem design':       'system design',
+    'python. ml':         'ml',           
+}
+
+def normalizer(skills) -> list:
+    if pd.isna(skills):
+        return []
+    skill = [s.strip().lower() for s in skills.split(',') if s.strip()]
+    fixed = [SKILLS_FIX.get(s, s) for s in skill]
+    return list(dict.fromkeys(fixed))
+
+df['skill_list'] = df['tech_skills'].apply(normalizer)
+
+freq  = Counter(s for lst in df['skill_list'] for s in lst)
+VOCAB = sorted([s for s, c in freq.items() if c >= 2])
+
+def encoder(skill_list) -> list:
+    return [1 if lbl in skill_list else 0 for lbl in VOCAB]
+
+y = np.array([encoder(lst) for lst in df['skill_list']], dtype=np.float32)
+
+def apply_synonyms(text: str) -> str:
+    text = text.lower()
+    for phrase, canonical in sorted(SYNONYM_MAP.items(), key=lambda x: -len(x[0])):
+        text = text.replace(phrase, canonical)
+    return text
+
+jd_input = (
+    df['job_desc'].fillna('').apply(apply_synonyms) + ' ' +
+    df['role'].fillna('').str.lower() + ' ' +
+    df['type'].fillna('').str.lower()
+)
+
+vectorizer = TfidfVectorizer(
+    max_features=150,
+    stop_words='english',
+    ngram_range=(1, 2),
+    min_df=2,
+)
+X = vectorizer.fit_transform(jd_input).toarray().astype(np.float32)
+
+X_train, X_test, y_train, y_test, idx_train, idx_test = train_test_split(
+    X, y, np.arange(len(df)),
+    test_size=0.2,
+    random_state=42
+)
+
+print(f"Dataset: {len(df)} rows | Vocab: {len(VOCAB)} labels | "
+      f"TF-IDF features: {X.shape[1]}")
+print(f"Train: {len(X_train)} | Test: {len(X_test)}")
+
+# Save artifacts relative to this script location so pipeline.py can be run from repo root
+OUT_DIR = Path(__file__).resolve().parent
+
+np.savez(
+    OUT_DIR / 'prepared_data.npz',
+    X_train=X_train,
+    X_test=X_test,
+    y_train=y_train,
+    y_test=y_test,
+    idx_train=idx_train,
+    idx_test=idx_test,
+)
+
+with open(OUT_DIR / 'label_vocab.json', 'w') as f:
+    json.dump(VOCAB, f, indent=2)
+
+with open(OUT_DIR / 'vectorizer.pkl', 'wb') as f:
+    pickle.dump(vectorizer, f)
+
+print("Successfully Vectorized and Pickled Data")

model/prep/label_vocab.json

@@ -0,0 +1,50 @@
+[
+  ".net",
+  "agents",
+  "anthropic /openai sdks",
+  "apis",
+  "autogen",
+  "aws/azure",
+  "c",
+  "c#",
+  "c++",
+  "ci/cd",
+  "crewai",
+  "django",
+  "docker",
+  "feature engineering",
+  "full stack",
+  "genai",
+  "git",
+  "github",
+  "hugging face",
+  "java",
+  "javascript",
+  "kubernetes",
+  "langchain",
+  "langgraph",
+  "llamaindex",
+  "llms",
+  "mcp",
+  "ml",
+  "mlflow",
+  "mlops",
+  "model evaluation",
+  "model training",
+  "n8n",
+  "nlp",
+  "numpy",
+  "openai",
+  "pandas",
+  "powerbi",
+  "prompt engineering",
+  "python",
+  "r",
+  "rag",
+  "react",
+  "scikit-learn",
+  "sql",
+  "system design",
+  "tensorflow/pytorch",
+  "vectordb"
+]

model/prep/prepared_data.npz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:40512906662cce58a30dfe702fe6211ed2632ec5074ed09a5f46beed4dea39fc
+size 169500

model/prep/sym_map.py

@@ -0,0 +1,110 @@
+"""
+sym_map.py - All synonyms for the TF-IDF Vectorizer
+"""
+
+SYNONYM_MAP = {
+    # docker 
+    'containeriz':              'docker',
+    'containerize':             'docker',
+
+    # git 
+    'version control':          'git',
+    'source control':           'git',
+
+    # github 
+    'gitlab':                   'github',
+    'bitbucket':                'github',
+    'pull request':             'github',
+
+    # ci/cd 
+    'infrastructure-as-code':   'ci/cd',
+    'continuous integration':   'ci/cd',
+    'continuous deployment':    'ci/cd',
+    'continuous delivery':      'ci/cd',
+    'github actions':           'ci/cd',
+    'gitlab ci':                'ci/cd',
+    'jenkins':                  'ci/cd',
+    'devops':                   'ci/cd',
+    'cicd':                     'ci/cd',
+
+    # genai 
+    'generative ai':            'genai',
+    'frontier model':           'genai',
+    'foundation model':         'genai',
+    'gen ai':                   'genai',
+    'gemini':                   'genai',
+    'claude':                   'genai',
+    'gpt':                      'genai',
+
+    # agents 
+    'multi-agent':              'agents',
+    'orchestrat':               'agents',
+    'agentic':                  'agents',
+    'copilot':                  'agents',
+
+    # mcp
+    'model context protocol':   'mcp',
+    'protocol wrapper':         'mcp',
+    'function calling':         'mcp',
+    'tool call':                'mcp',
+
+    # prompt engineering 
+    'prompt engineer':          'prompt engineering',
+    'chain-of-thought':         'prompt engineering',
+    'system prompt':            'prompt engineering',
+    'few-shot':                 'prompt engineering',
+    'zero-shot':                'prompt engineering',
+    'prompt design':            'prompt engineering',
+
+    # mlops 
+    'experiment track':         'mlops',
+    'model monitor':            'mlops',
+    'model deploy':             'mlops',
+    'model registry':           'mlops',
+    'ml ops':                   'mlops',
+
+    # kubernetes   
+    'k8s':                      'kubernetes',
+    'helm':                     'kubernetes',
+    'eks':                      'kubernetes',
+    'aks':                      'kubernetes',
+    'gke':                      'kubernetes',
+
+    # sql 
+    'postgresql':               'sql',
+    'postgres':                 'sql',
+    'pgvector':                 'sql',
+    'snowflake':                'sql',
+    'databricks':               'sql',
+    'mysql':                    'sql',
+    'nosql':                    'sql',
+
+    # vectordb 
+    'azure ai search':          'vectordb',
+    'vector database':          'vectordb',
+    'vector store':             'vectordb',
+    'embedding store':          'vectordb',
+    'pinecone':                 'vectordb',
+    'chromadb':                 'vectordb',
+    'weaviate':                 'vectordb',
+    'qdrant':                   'vectordb',
+    'faiss':                    'vectordb',
+    'milvus':                   'vectordb',
+
+    # nlp 
+    'natural language':         'nlp',
+    'named entity':             'nlp',
+    'text classification':      'nlp',
+
+    # aws/azure 
+    'amazon web services':      'aws/azure',
+    'azure openai':             'aws/azure',
+    'google cloud':             'aws/azure',
+    'ai foundry':               'aws/azure',
+    'sagemaker':                'aws/azure',
+    'bedrock':                  'aws/azure',
+    'gcp':                      'aws/azure',
+    'lambda':                   'aws/azure',
+    'ec2':                      'aws/azure',
+    's3':                       'aws/azure',
+}

model/prep/test.py

@@ -0,0 +1,10 @@
+"""
+test.py - Vectorizer test for maps
+"""
+
+import pickle
+
+with open('vectorizer.pkl', 'rb') as f:
+    v = pickle.load(f)
+print('ci/cd' in v.get_feature_names_out())
+print('infrastructure-as-code' in v.get_feature_names_out())

model/prep/vectorizer.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72474e5fa57be99dd8f111f6521ff733aafc9c479b44659f9d2ae7c9d7f6b4d4
+size 6583

model_out/skill_classifier.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6783af59ede98090521397e45131ac136f65e035d7c425027cf9307e5e4cd7ad
+size 28279

model_out/training_history.json

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notebooks/01_EDA.ipynb

@@ -0,0 +1,695 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "cdd7b111",
+   "metadata": {},
+   "source": [
+    "### EDA and Data Lookup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "50ddeacc",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:31.659870Z",
+     "iopub.status.busy": "2026-07-05T07:01:31.659399Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.505941Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.504134Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "599b8d5d",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.510739Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.510245Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.593359Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.591374Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>role</th>\n",
+       "      <th>type</th>\n",
+       "      <th>job_desc</th>\n",
+       "      <th>year</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>experience</th>\n",
+       "      <th>tech_skills</th>\n",
+       "      <th>soft_skills</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Final year students / recent graduates in CS, ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, LangChain, Hugging Face, OpenAI API</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Proficiency in Python and comfort working with...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, APIs, LLMs, Prompt Engineering, LangCh...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Strong interest in AI and a willingness to lea...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, APIs, M...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>6+ years full-stack software engineering exper...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, SQL, AP...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>AI/ML models, Python, Core ML concepts, ML fra...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   id         role        type  \\\n",
+       "0   1  AI Engineer  Internship   \n",
+       "1   2  AI Engineer  Internship   \n",
+       "2   3  AI Engineer  Internship   \n",
+       "3   4  AI Engineer      Senior   \n",
+       "4   5  AI Engineer      Junior   \n",
+       "\n",
+       "                                            job_desc  year qualification  \\\n",
+       "0  Final year students / recent graduates in CS, ...  2026     Bachelors   \n",
+       "1  Proficiency in Python and comfort working with...  2026     Bachelors   \n",
+       "2  Strong interest in AI and a willingness to lea...  2026     Bachelors   \n",
+       "3  6+ years full-stack software engineering exper...  2026           NaN   \n",
+       "4  AI/ML models, Python, Core ML concepts, ML fra...  2026     Bachelors   \n",
+       "\n",
+       "  experience                                        tech_skills  \\\n",
+       "0          0    Python, ML, LangChain, Hugging Face, OpenAI API   \n",
+       "1          0  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "2          0  Python, Javascript, React, Full Stack, APIs, M...   \n",
+       "3       5-10  Python, Javascript, React, Full Stack, SQL, AP...   \n",
+       "4        0-1  Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...   \n",
+       "\n",
+       "                      soft_skills  \n",
+       "0  Communication, Problem Solving  \n",
+       "1  Communication, Problem Solving  \n",
+       "2  Communication, Problem Solving  \n",
+       "3  Communication, Problem Solving  \n",
+       "4  Communication, Problem Solving  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(r\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\raw\\Job_descriptions.csv\")\n",
+    "df.head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4addff6c",
+   "metadata": {},
+   "source": [
+    "### EDA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4f762807",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.596937Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.596513Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.606232Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.605189Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "id               210\n",
+       "role             210\n",
+       "type             210\n",
+       "job_desc         210\n",
+       "year             210\n",
+       "qualification    210\n",
+       "experience       210\n",
+       "tech_skills      210\n",
+       "soft_skills      210\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().count()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e9aab529",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.610391Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.609903Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.628368Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.627211Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>210.000000</td>\n",
+       "      <td>210.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>105.823810</td>\n",
+       "      <td>2026.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>60.033264</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2026.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>54.250000</td>\n",
+       "      <td>2026.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>106.500000</td>\n",
+       "      <td>2026.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>158.750000</td>\n",
+       "      <td>2026.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>201.000000</td>\n",
+       "      <td>2026.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               id    year\n",
+       "count  210.000000   210.0\n",
+       "mean   105.823810  2026.0\n",
+       "std     60.033264     0.0\n",
+       "min      1.000000  2026.0\n",
+       "25%     54.250000  2026.0\n",
+       "50%    106.500000  2026.0\n",
+       "75%    158.750000  2026.0\n",
+       "max    201.000000  2026.0"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "e21cc8a1",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.632751Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.632391Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.652382Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.650828Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "RangeIndex: 210 entries, 0 to 209\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column         Non-Null Count  Dtype\n",
+      "---  ------         --------------  -----\n",
+      " 0   id             210 non-null    int64\n",
+      " 1   role           210 non-null    str  \n",
+      " 2   type           210 non-null    str  \n",
+      " 3   job_desc       210 non-null    str  \n",
+      " 4   year           210 non-null    int64\n",
+      " 5   qualification  171 non-null    str  \n",
+      " 6   experience     210 non-null    str  \n",
+      " 7   tech_skills    210 non-null    str  \n",
+      " 8   soft_skills    210 non-null    str  \n",
+      "dtypes: int64(2), str(7)\n",
+      "memory usage: 14.9 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "d3f29f62",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.656033Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.655547Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.671172Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.669846Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>role</th>\n",
+       "      <th>type</th>\n",
+       "      <th>job_desc</th>\n",
+       "      <th>year</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>experience</th>\n",
+       "      <th>tech_skills</th>\n",
+       "      <th>soft_skills</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Final year students / recent graduates in CS, ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, LangChain, Hugging Face, OpenAI API</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Proficiency in Python and comfort working with...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, APIs, LLMs, Prompt Engineering, LangCh...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Strong interest in AI and a willingness to lea...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, APIs, M...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>6+ years full-stack software engineering exper...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, SQL, AP...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>AI/ML models, Python, Core ML concepts, ML fra...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   id         role        type  \\\n",
+       "0   1  AI Engineer  Internship   \n",
+       "1   2  AI Engineer  Internship   \n",
+       "2   3  AI Engineer  Internship   \n",
+       "3   4  AI Engineer      Senior   \n",
+       "4   5  AI Engineer      Junior   \n",
+       "\n",
+       "                                            job_desc  year  qualification  \\\n",
+       "0  Final year students / recent graduates in CS, ...  2026      Bachelors   \n",
+       "1  Proficiency in Python and comfort working with...  2026      Bachelors   \n",
+       "2  Strong interest in AI and a willingness to lea...  2026      Bachelors   \n",
+       "3  6+ years full-stack software engineering exper...  2026  Not Specified   \n",
+       "4  AI/ML models, Python, Core ML concepts, ML fra...  2026      Bachelors   \n",
+       "\n",
+       "  experience                                        tech_skills  \\\n",
+       "0          0    Python, ML, LangChain, Hugging Face, OpenAI API   \n",
+       "1          0  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "2          0  Python, Javascript, React, Full Stack, APIs, M...   \n",
+       "3       5-10  Python, Javascript, React, Full Stack, SQL, AP...   \n",
+       "4        0-1  Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...   \n",
+       "\n",
+       "                      soft_skills  \n",
+       "0  Communication, Problem Solving  \n",
+       "1  Communication, Problem Solving  \n",
+       "2  Communication, Problem Solving  \n",
+       "3  Communication, Problem Solving  \n",
+       "4  Communication, Problem Solving  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.fillna('Not Specified', inplace=True).head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "719b05fd",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.675240Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.674649Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.687557Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.686187Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "id               200\n",
+       "role               2\n",
+       "type               3\n",
+       "job_desc         208\n",
+       "year               1\n",
+       "qualification      4\n",
+       "experience         6\n",
+       "tech_skills      205\n",
+       "soft_skills        8\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.nunique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "b61eed8e",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.691255Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.690871Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.698027Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.696400Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<StringArray>\n",
+      "['AI Engineer', 'AI Developer']\n",
+      "Length: 2, dtype: str\n"
+     ]
+    }
+   ],
+   "source": [
+    "role_unique = df['role'].unique()\n",
+    "print(role_unique)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "456c159c",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.701548Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.701190Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.707737Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.706063Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<StringArray>\n",
+      "['Internship', 'Senior', 'Junior']\n",
+      "Length: 3, dtype: str\n"
+     ]
+    }
+   ],
+   "source": [
+    "type_unique = df['type'].unique()\n",
+    "print(type_unique)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0748fbf2",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.711265Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.710734Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.717419Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.715670Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<StringArray>\n",
+      "['0', '5-10', '0-1', '1-5', '15+', '10-15']\n",
+      "Length: 6, dtype: str\n"
+     ]
+    }
+   ],
+   "source": [
+    "experience_unique = df['experience'].unique()\n",
+    "print(experience_unique)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "2b03a4a0",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:32.720912Z",
+     "iopub.status.busy": "2026-07-05T07:01:32.720366Z",
+     "iopub.status.idle": "2026-07-05T07:01:32.739180Z",
+     "shell.execute_reply": "2026-07-05T07:01:32.737432Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "<>:1: SyntaxWarning: \"\\P\" is an invalid escape sequence. Such sequences will not work in the future. Did you mean \"\\\\P\"? A raw string is also an option.\n",
+      "<>:1: SyntaxWarning: \"\\P\" is an invalid escape sequence. Such sequences will not work in the future. Did you mean \"\\\\P\"? A raw string is also an option.\n",
+      "C:\\Users\\Akshay\\AppData\\Local\\Temp\\ipykernel_2816\\2088954097.py:1: SyntaxWarning: \"\\P\" is an invalid escape sequence. Such sequences will not work in the future. Did you mean \"\\\\P\"? A raw string is also an option.\n",
+      "  df.to_csv(\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\clean\\cleaned_job_descriptions.csv\", index=False)\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.to_csv(\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\clean\\cleaned_job_descriptions.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "284aa9f4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.14.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

notebooks/02_Data_Engineering.ipynb

@@ -0,0 +1,1802 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f6a59636",
+   "metadata": {},
+   "source": [
+    "### Data Engineering"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "93fc3161",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.173273Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.172907Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.847508Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.846478Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "11f11c89",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.851035Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.850637Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.877988Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.876489Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(r\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\clean\\cleaned_job_descriptions.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f4334454",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.881169Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.880735Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.902386Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.899923Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>role</th>\n",
+       "      <th>type</th>\n",
+       "      <th>job_desc</th>\n",
+       "      <th>year</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>experience</th>\n",
+       "      <th>tech_skills</th>\n",
+       "      <th>soft_skills</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Final year students / recent graduates in CS, ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, LangChain, Hugging Face, OpenAI API</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Proficiency in Python and comfort working with...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, APIs, LLMs, Prompt Engineering, LangCh...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Strong interest in AI and a willingness to lea...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, APIs, M...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>6+ years full-stack software engineering exper...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, SQL, AP...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>AI/ML models, Python, Core ML concepts, ML fra...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>4–5 years of proven development experience in ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, C++, Java, TensorFlow/PyTorch, vLLM, O...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>5-10 years overall experience\\n3+ years of han...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, SQL, PowerBI, SAP, LLMs, Prompt Engine...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Proficiency in C/C++ and python programming\\nH...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, C, C++, Sytem Design, Model Evaluation</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python\\nMachine Learning Fundamentals\\nLarge L...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, LLMs, Prompt Engineering, APIs, La...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Solid understanding of LLMs, tokenization, tra...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Pandas, NumPyHugging Face, LangChain, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   id         role        type  \\\n",
+       "0   1  AI Engineer  Internship   \n",
+       "1   2  AI Engineer  Internship   \n",
+       "2   3  AI Engineer  Internship   \n",
+       "3   4  AI Engineer      Senior   \n",
+       "4   5  AI Engineer      Junior   \n",
+       "5   6  AI Engineer      Junior   \n",
+       "6   7  AI Engineer      Senior   \n",
+       "7   8  AI Engineer      Junior   \n",
+       "8   9  AI Engineer  Internship   \n",
+       "9  10  AI Engineer  Internship   \n",
+       "\n",
+       "                                            job_desc  year  qualification  \\\n",
+       "0  Final year students / recent graduates in CS, ...  2026      Bachelors   \n",
+       "1  Proficiency in Python and comfort working with...  2026      Bachelors   \n",
+       "2  Strong interest in AI and a willingness to lea...  2026      Bachelors   \n",
+       "3  6+ years full-stack software engineering exper...  2026  Not Specified   \n",
+       "4  AI/ML models, Python, Core ML concepts, ML fra...  2026      Bachelors   \n",
+       "5  4–5 years of proven development experience in ...  2026      Bachelors   \n",
+       "6  5-10 years overall experience\\n3+ years of han...  2026  Not Specified   \n",
+       "7  Proficiency in C/C++ and python programming\\nH...  2026      Bachelors   \n",
+       "8  Python\\nMachine Learning Fundamentals\\nLarge L...  2026      Bachelors   \n",
+       "9  Solid understanding of LLMs, tokenization, tra...  2026      Bachelors   \n",
+       "\n",
+       "  experience                                        tech_skills  \\\n",
+       "0          0    Python, ML, LangChain, Hugging Face, OpenAI API   \n",
+       "1          0  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "2          0  Python, Javascript, React, Full Stack, APIs, M...   \n",
+       "3       5-10  Python, Javascript, React, Full Stack, SQL, AP...   \n",
+       "4        0-1  Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...   \n",
+       "5       5-10  Python, C++, Java, TensorFlow/PyTorch, vLLM, O...   \n",
+       "6       5-10  Python, SQL, PowerBI, SAP, LLMs, Prompt Engine...   \n",
+       "7        0-1     Python, C, C++, Sytem Design, Model Evaluation   \n",
+       "8          0  Python, ML, LLMs, Prompt Engineering, APIs, La...   \n",
+       "9          0  Python, Pandas, NumPyHugging Face, LangChain, ...   \n",
+       "\n",
+       "                      soft_skills  \n",
+       "0  Communication, Problem Solving  \n",
+       "1  Communication, Problem Solving  \n",
+       "2  Communication, Problem Solving  \n",
+       "3  Communication, Problem Solving  \n",
+       "4  Communication, Problem Solving  \n",
+       "5  Communication, Problem Solving  \n",
+       "6  Communication, Problem Solving  \n",
+       "7  Communication, Problem Solving  \n",
+       "8  Communication, Problem Solving  \n",
+       "9  Communication, Problem Solving  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f3e09086",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.915808Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.915514Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.926306Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.925020Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "RangeIndex: 210 entries, 0 to 209\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column         Non-Null Count  Dtype\n",
+      "---  ------         --------------  -----\n",
+      " 0   id             210 non-null    int64\n",
+      " 1   role           210 non-null    str  \n",
+      " 2   type           210 non-null    str  \n",
+      " 3   job_desc       210 non-null    str  \n",
+      " 4   year           210 non-null    int64\n",
+      " 5   qualification  210 non-null    str  \n",
+      " 6   experience     210 non-null    str  \n",
+      " 7   tech_skills    210 non-null    str  \n",
+      " 8   soft_skills    210 non-null    str  \n",
+      "dtypes: int64(2), str(7)\n",
+      "memory usage: 14.9 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "092d1bf5",
+   "metadata": {
+    "execution": {
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+     "shell.execute_reply": "2026-07-05T07:01:35.943172Z"
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+       "    <tr>\n",
+       "      <th>2</th>\n",
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+       "      <td>0</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, APIs, M...</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python\\nMachine Learning Fundamentals\\nLarge L...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, LLMs, Prompt Engineering, APIs, La...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Solid understanding of LLMs, tokenization, tra...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Pandas, NumPyHugging Face, LangChain, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Basic to intermediate Python programming skill...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, GenAI, APIs, Git, Prompt Engineeri...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>27</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python Skills: You should be very comfortable ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Javascript, React, LLMs, VectorDB, Lan...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>28</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Exposure to Full-Stack Development (frontend a...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Git, Github, Full Stack, LLMs, APIs, G...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>29</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python, TensorFlow, PyTorch, Scikit-learn, Num...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, TensorFlow/PyTorch, Scikit-Learn, NumP...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>30</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Recently completed a degree in Computer Scienc...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, GenAI, LLMs, RAG, Prompt Engineering, ...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    id          role        type  \\\n",
+       "0    1   AI Engineer  Internship   \n",
+       "1    2   AI Engineer  Internship   \n",
+       "2    3   AI Engineer  Internship   \n",
+       "8    9   AI Engineer  Internship   \n",
+       "9   10   AI Engineer  Internship   \n",
+       "12  13  AI Developer  Internship   \n",
+       "25  27   AI Engineer  Internship   \n",
+       "26  28   AI Engineer  Internship   \n",
+       "27  29   AI Engineer  Internship   \n",
+       "28  30   AI Engineer  Internship   \n",
+       "\n",
+       "                                             job_desc  year qualification  \\\n",
+       "0   Final year students / recent graduates in CS, ...  2026     Bachelors   \n",
+       "1   Proficiency in Python and comfort working with...  2026     Bachelors   \n",
+       "2   Strong interest in AI and a willingness to lea...  2026     Bachelors   \n",
+       "8   Python\\nMachine Learning Fundamentals\\nLarge L...  2026     Bachelors   \n",
+       "9   Solid understanding of LLMs, tokenization, tra...  2026     Bachelors   \n",
+       "12  Basic to intermediate Python programming skill...  2026     Bachelors   \n",
+       "25  Python Skills: You should be very comfortable ...  2026     Bachelors   \n",
+       "26  Exposure to Full-Stack Development (frontend a...  2026     Bachelors   \n",
+       "27  Python, TensorFlow, PyTorch, Scikit-learn, Num...  2026     Bachelors   \n",
+       "28  Recently completed a degree in Computer Scienc...  2026     Bachelors   \n",
+       "\n",
+       "   experience                                        tech_skills  \\\n",
+       "0           0    Python, ML, LangChain, Hugging Face, OpenAI API   \n",
+       "1           0  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "2           0  Python, Javascript, React, Full Stack, APIs, M...   \n",
+       "8           0  Python, ML, LLMs, Prompt Engineering, APIs, La...   \n",
+       "9           0  Python, Pandas, NumPyHugging Face, LangChain, ...   \n",
+       "12          0  Python, ML, GenAI, APIs, Git, Prompt Engineeri...   \n",
+       "25          0  Python, Javascript, React, LLMs, VectorDB, Lan...   \n",
+       "26          0  Python, Git, Github, Full Stack, LLMs, APIs, G...   \n",
+       "27          0  Python, TensorFlow/PyTorch, Scikit-Learn, NumP...   \n",
+       "28          0  Python, GenAI, LLMs, RAG, Prompt Engineering, ...   \n",
+       "\n",
+       "                                          soft_skills  \n",
+       "0                      Communication, Problem Solving  \n",
+       "1                      Communication, Problem Solving  \n",
+       "2                      Communication, Problem Solving  \n",
+       "8                      Communication, Problem Solving  \n",
+       "9                      Communication, Problem Solving  \n",
+       "12  Communication, Problem Solving, Analytical Skills  \n",
+       "25                     Communication, Problem Solving  \n",
+       "26  Communication, Problem Solving, Analytical Skills  \n",
+       "27                     Communication, Problem Solving  \n",
+       "28  Communication, Problem Solving, Analytical Skills  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_intern = df[df['type'].eq('Internship')]\n",
+    "df_intern.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2d952c07",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.947674Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.947366Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.956168Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.955280Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "Index: 70 entries, 0 to 209\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column         Non-Null Count  Dtype\n",
+      "---  ------         --------------  -----\n",
+      " 0   id             70 non-null     int64\n",
+      " 1   role           70 non-null     str  \n",
+      " 2   type           70 non-null     str  \n",
+      " 3   job_desc       70 non-null     str  \n",
+      " 4   year           70 non-null     int64\n",
+      " 5   qualification  70 non-null     str  \n",
+      " 6   experience     70 non-null     str  \n",
+      " 7   tech_skills    70 non-null     str  \n",
+      " 8   soft_skills    70 non-null     str  \n",
+      "dtypes: int64(2), str(7)\n",
+      "memory usage: 5.5 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_intern.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8a6daa80",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.959463Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.959079Z",
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+     "shell.execute_reply": "2026-07-05T07:01:35.971478Z"
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+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python\\nMachine Learning Fundamentals\\nLarge L...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, LLMs, Prompt Engineering, APIs, La...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Solid understanding of LLMs, tokenization, tra...</td>\n",
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+       "      <td>Python, Pandas, NumPyHugging Face, LangChain, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Basic to intermediate Python programming skill...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, GenAI, APIs, Git, Prompt Engineeri...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>27</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python Skills: You should be very comfortable ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Javascript, React, LLMs, VectorDB, Lan...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>28</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Exposure to Full-Stack Development (frontend a...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, Git, Github, Full Stack, LLMs, APIs, G...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>29</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Python, TensorFlow, PyTorch, Scikit-learn, Num...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, TensorFlow/PyTorch, Scikit-Learn, NumP...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>30</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Recently completed a degree in Computer Scienc...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, GenAI, LLMs, RAG, Prompt Engineering, ...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    id          role        type  \\\n",
+       "0    1   AI Engineer  Internship   \n",
+       "1    2   AI Engineer  Internship   \n",
+       "2    3   AI Engineer  Internship   \n",
+       "8    9   AI Engineer  Internship   \n",
+       "9   10   AI Engineer  Internship   \n",
+       "12  13  AI Developer  Internship   \n",
+       "25  27   AI Engineer  Internship   \n",
+       "26  28   AI Engineer  Internship   \n",
+       "27  29   AI Engineer  Internship   \n",
+       "28  30   AI Engineer  Internship   \n",
+       "\n",
+       "                                             job_desc  year qualification  \\\n",
+       "0   Final year students / recent graduates in CS, ...  2026     Bachelors   \n",
+       "1   Proficiency in Python and comfort working with...  2026     Bachelors   \n",
+       "2   Strong interest in AI and a willingness to lea...  2026     Bachelors   \n",
+       "8   Python\\nMachine Learning Fundamentals\\nLarge L...  2026     Bachelors   \n",
+       "9   Solid understanding of LLMs, tokenization, tra...  2026     Bachelors   \n",
+       "12  Basic to intermediate Python programming skill...  2026     Bachelors   \n",
+       "25  Python Skills: You should be very comfortable ...  2026     Bachelors   \n",
+       "26  Exposure to Full-Stack Development (frontend a...  2026     Bachelors   \n",
+       "27  Python, TensorFlow, PyTorch, Scikit-learn, Num...  2026     Bachelors   \n",
+       "28  Recently completed a degree in Computer Scienc...  2026     Bachelors   \n",
+       "\n",
+       "   experience                                        tech_skills  \\\n",
+       "0           0    Python, ML, LangChain, Hugging Face, OpenAI API   \n",
+       "1           0  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "2           0  Python, Javascript, React, Full Stack, APIs, M...   \n",
+       "8           0  Python, ML, LLMs, Prompt Engineering, APIs, La...   \n",
+       "9           0  Python, Pandas, NumPyHugging Face, LangChain, ...   \n",
+       "12          0  Python, ML, GenAI, APIs, Git, Prompt Engineeri...   \n",
+       "25          0  Python, Javascript, React, LLMs, VectorDB, Lan...   \n",
+       "26          0  Python, Git, Github, Full Stack, LLMs, APIs, G...   \n",
+       "27          0  Python, TensorFlow/PyTorch, Scikit-Learn, NumP...   \n",
+       "28          0  Python, GenAI, LLMs, RAG, Prompt Engineering, ...   \n",
+       "\n",
+       "                                          soft_skills  \n",
+       "0                      Communication, Problem Solving  \n",
+       "1                      Communication, Problem Solving  \n",
+       "2                      Communication, Problem Solving  \n",
+       "8                      Communication, Problem Solving  \n",
+       "9                      Communication, Problem Solving  \n",
+       "12  Communication, Problem Solving, Analytical Skills  \n",
+       "25                     Communication, Problem Solving  \n",
+       "26  Communication, Problem Solving, Analytical Skills  \n",
+       "27                     Communication, Problem Solving  \n",
+       "28  Communication, Problem Solving, Analytical Skills  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_intern = df_intern[df_intern['qualification'].eq('Bachelors')]\n",
+    "df_intern.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "e0aca5d6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.975495Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.975112Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.984842Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.983362Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "Index: 69 entries, 0 to 209\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column         Non-Null Count  Dtype\n",
+      "---  ------         --------------  -----\n",
+      " 0   id             69 non-null     int64\n",
+      " 1   role           69 non-null     str  \n",
+      " 2   type           69 non-null     str  \n",
+      " 3   job_desc       69 non-null     str  \n",
+      " 4   year           69 non-null     int64\n",
+      " 5   qualification  69 non-null     str  \n",
+      " 6   experience     69 non-null     str  \n",
+      " 7   tech_skills    69 non-null     str  \n",
+      " 8   soft_skills    69 non-null     str  \n",
+      "dtypes: int64(2), str(7)\n",
+      "memory usage: 5.4 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_intern.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "6082e0b2",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:35.987693Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.987306Z",
+     "iopub.status.idle": "2026-07-05T07:01:35.997366Z",
+     "shell.execute_reply": "2026-07-05T07:01:35.996167Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df_intern.to_csv(r\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\clean\\cleaned_job_descriptions_internships.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "52321146",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.000211Z",
+     "iopub.status.busy": "2026-07-05T07:01:35.999842Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.014067Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.012721Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>role</th>\n",
+       "      <th>type</th>\n",
+       "      <th>job_desc</th>\n",
+       "      <th>year</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>experience</th>\n",
+       "      <th>tech_skills</th>\n",
+       "      <th>soft_skills</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>AI/ML models, Python, Core ML concepts, ML fra...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>4–5 years of proven development experience in ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, C++, Java, TensorFlow/PyTorch, vLLM, O...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Proficiency in C/C++ and python programming\\nH...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, C, C++, Sytem Design, Model Evaluation</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>14</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Basic understanding of AI, Machine Learning, o...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, ML, APIs</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>16</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Docker / Containerization\\nAWS / Azure / GCP e...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, ML, Docker, AWS/Azure,</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>1+ years of experience in AI, LLMs, automation...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>1-5</td>\n",
+       "      <td>Python, APIs, LLMs, Prompt Engineering, LangCh...</td>\n",
+       "      <td>Communication, Problem Solving, Ownership</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Strong Python programming\\nExperience with Fas...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, React, Javascript, APIs, AWS/Azure, LL...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>19</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Degree in Computer Science, AI, or a related f...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, Javascript,&nbsp;&nbsp;LLMs, Prompt Engineering,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>22</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Strong programming skills in Python.\\nExperien...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, LLMs, Prompt Engineering, RAG, TensorF...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>26</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Strong hands-on experience in Python programmi...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, APIs, GenAI, LLMs, Pandas, NumPy, Scik...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    id          role    type  \\\n",
+       "4    5   AI Engineer  Junior   \n",
+       "5    6   AI Engineer  Junior   \n",
+       "7    8   AI Engineer  Junior   \n",
+       "13  14   AI Engineer  Junior   \n",
+       "15  16   AI Engineer  Junior   \n",
+       "16  17   AI Engineer  Junior   \n",
+       "17  18  AI Developer  Junior   \n",
+       "18  19   AI Engineer  Junior   \n",
+       "21  22   AI Engineer  Junior   \n",
+       "24  26   AI Engineer  Junior   \n",
+       "\n",
+       "                                             job_desc  year qualification  \\\n",
+       "4   AI/ML models, Python, Core ML concepts, ML fra...  2026     Bachelors   \n",
+       "5   4–5 years of proven development experience in ...  2026     Bachelors   \n",
+       "7   Proficiency in C/C++ and python programming\\nH...  2026     Bachelors   \n",
+       "13  Basic understanding of AI, Machine Learning, o...  2026     Bachelors   \n",
+       "15  Docker / Containerization\\nAWS / Azure / GCP e...  2026     Bachelors   \n",
+       "16  1+ years of experience in AI, LLMs, automation...  2026     Bachelors   \n",
+       "17  Strong Python programming\\nExperience with Fas...  2026     Bachelors   \n",
+       "18  Degree in Computer Science, AI, or a related f...  2026     Bachelors   \n",
+       "21  Strong programming skills in Python.\\nExperien...  2026     Bachelors   \n",
+       "24  Strong hands-on experience in Python programmi...  2026     Bachelors   \n",
+       "\n",
+       "   experience                                        tech_skills  \\\n",
+       "4         0-1  Python, ML, TensorFlow/PyTorch, Scikit-Learn, ...   \n",
+       "5        5-10  Python, C++, Java, TensorFlow/PyTorch, vLLM, O...   \n",
+       "7         0-1     Python, C, C++, Sytem Design, Model Evaluation   \n",
+       "13        0-1                                   Python, ML, APIs   \n",
+       "15        0-1                    Python, ML, Docker, AWS/Azure,    \n",
+       "16        1-5  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "17        0-1  Python, React, Javascript, APIs, AWS/Azure, LL...   \n",
+       "18        0-1  Python, Javascript,  LLMs, Prompt Engineering,...   \n",
+       "21        0-1  Python, LLMs, Prompt Engineering, RAG, TensorF...   \n",
+       "24        0-1  Python, APIs, GenAI, LLMs, Pandas, NumPy, Scik...   \n",
+       "\n",
+       "                                  soft_skills  \n",
+       "4              Communication, Problem Solving  \n",
+       "5              Communication, Problem Solving  \n",
+       "7              Communication, Problem Solving  \n",
+       "13             Communication, Problem Solving  \n",
+       "15             Communication, Problem Solving  \n",
+       "16  Communication, Problem Solving, Ownership  \n",
+       "17             Communication, Problem Solving  \n",
+       "18             Communication, Problem Solving  \n",
+       "21             Communication, Problem Solving  \n",
+       "24             Communication, Problem Solving  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_junior = df[df['type'].eq('Junior')]\n",
+    "df_junior.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "80aac5d6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.016896Z",
+     "iopub.status.busy": "2026-07-05T07:01:36.016519Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.026257Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.024828Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "Index: 70 entries, 4 to 201\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column         Non-Null Count  Dtype\n",
+      "---  ------         --------------  -----\n",
+      " 0   id             70 non-null     int64\n",
+      " 1   role           70 non-null     str  \n",
+      " 2   type           70 non-null     str  \n",
+      " 3   job_desc       70 non-null     str  \n",
+      " 4   year           70 non-null     int64\n",
+      " 5   qualification  70 non-null     str  \n",
+      " 6   experience     70 non-null     str  \n",
+      " 7   tech_skills    70 non-null     str  \n",
+      " 8   soft_skills    70 non-null     str  \n",
+      "dtypes: int64(2), str(7)\n",
+      "memory usage: 5.5 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_junior.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "df08fe65",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.029188Z",
+     "iopub.status.busy": "2026-07-05T07:01:36.028794Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.037488Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.036372Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df_junior.to_csv(r\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\clean\\cleaned_job_descriptions_junior.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "746fb32f",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.040810Z",
+     "iopub.status.busy": "2026-07-05T07:01:36.040403Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.054688Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.053769Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>role</th>\n",
+       "      <th>type</th>\n",
+       "      <th>job_desc</th>\n",
+       "      <th>year</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>experience</th>\n",
+       "      <th>tech_skills</th>\n",
+       "      <th>soft_skills</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>6+ years full-stack software engineering exper...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Javascript, React, Full Stack, SQL, AP...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>5-10 years overall experience\\n3+ years of han...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, SQL, PowerBI, SAP, LLMs, Prompt Engine...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>4–6 years of experience in Data Science / Mach...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Scikit-Learn, Pandas, NumPy, ML, LLMs,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>Bachelor's or Master's degree in Computer Scie...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors/Masters</td>\n",
+       "      <td>1-5</td>\n",
+       "      <td>Python, ML, APIs, GenAI, LangChain, LangGraph,...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>4–6 years of experience in Data Science / Mach...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, ML, Pandas, NumPy, Scikit-Learn, GenAI...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>20</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>Proven track record with at least 5 years of e...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>1-5</td>\n",
+       "      <td>Python, ML, NLP, MLOps, Feature Engineering, A...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>21</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>5+ years overall experience in software develo...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, APIs, LLMs, Prompt Engineering, LangCh...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>24</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>Core Software Engineering (Required)\\nStrong h...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Javascript, AWS/Azure, VectorDB, LLMs,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>25</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>15+ years of overall IT experience\\nStrong exp...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>15+</td>\n",
+       "      <td>Python, ML, APIs, AWS/Azure, CI/CD, Github, Git,</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>31</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>trong hands-on experience in Python backend de...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, LangChain, LangGraph, CrewAI, AutoGen,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>32</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>To qualify for the role you must have B.E/ B.T...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Masters</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python,&nbsp;&nbsp;ML, AWS/Azure, SQL, Docker, Kubernete...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>33</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>• 3–6 years of software development experience...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, APIs, SQL, LLMs, Prompt Engineering, R...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>34</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>- Experience in publishing research or contrib...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Masters</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, GenAI, LLMs</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>42</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>Python · JS/TS · Neo4j/Cypher · MongoDB · Post...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>1-5</td>\n",
+       "      <td>Python, Javascript, SQL, LLMs, APIs, VectorDB,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>44</td>\n",
+       "      <td>AI Engineer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>You will focus on creating reusable agent arch...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, ML, APIs, LLMs, LangChain, LangGraph, ...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    id          role    type  \\\n",
+       "3    4   AI Engineer  Senior   \n",
+       "6    7   AI Engineer  Senior   \n",
+       "10  11   AI Engineer  Senior   \n",
+       "11  12   AI Engineer  Senior   \n",
+       "14  15   AI Engineer  Senior   \n",
+       "19  20   AI Engineer  Senior   \n",
+       "20  21   AI Engineer  Senior   \n",
+       "22  24  AI Developer  Senior   \n",
+       "23  25   AI Engineer  Senior   \n",
+       "29  31  AI Developer  Senior   \n",
+       "30  32  AI Developer  Senior   \n",
+       "31  33  AI Developer  Senior   \n",
+       "32  34   AI Engineer  Senior   \n",
+       "40  42   AI Engineer  Senior   \n",
+       "42  44   AI Engineer  Senior   \n",
+       "\n",
+       "                                             job_desc  year  \\\n",
+       "3   6+ years full-stack software engineering exper...  2026   \n",
+       "6   5-10 years overall experience\\n3+ years of han...  2026   \n",
+       "10  4–6 years of experience in Data Science / Mach...  2026   \n",
+       "11  Bachelor's or Master's degree in Computer Scie...  2026   \n",
+       "14  4–6 years of experience in Data Science / Mach...  2026   \n",
+       "19  Proven track record with at least 5 years of e...  2026   \n",
+       "20  5+ years overall experience in software develo...  2026   \n",
+       "22  Core Software Engineering (Required)\\nStrong h...  2026   \n",
+       "23  15+ years of overall IT experience\\nStrong exp...  2026   \n",
+       "29  trong hands-on experience in Python backend de...  2026   \n",
+       "30  To qualify for the role you must have B.E/ B.T...  2026   \n",
+       "31  • 3–6 years of software development experience...  2026   \n",
+       "32  - Experience in publishing research or contrib...  2026   \n",
+       "40  Python · JS/TS · Neo4j/Cypher · MongoDB · Post...  2026   \n",
+       "42  You will focus on creating reusable agent arch...  2026   \n",
+       "\n",
+       "        qualification experience  \\\n",
+       "3       Not Specified       5-10   \n",
+       "6       Not Specified       5-10   \n",
+       "10      Not Specified       5-10   \n",
+       "11  Bachelors/Masters        1-5   \n",
+       "14      Not Specified       5-10   \n",
+       "19      Not Specified        1-5   \n",
+       "20      Not Specified       5-10   \n",
+       "22      Not Specified       5-10   \n",
+       "23      Not Specified        15+   \n",
+       "29          Bachelors       5-10   \n",
+       "30            Masters       5-10   \n",
+       "31      Not Specified       5-10   \n",
+       "32            Masters       5-10   \n",
+       "40      Not Specified        1-5   \n",
+       "42      Not Specified       5-10   \n",
+       "\n",
+       "                                          tech_skills  \\\n",
+       "3   Python, Javascript, React, Full Stack, SQL, AP...   \n",
+       "6   Python, SQL, PowerBI, SAP, LLMs, Prompt Engine...   \n",
+       "10  Python, Scikit-Learn, Pandas, NumPy, ML, LLMs,...   \n",
+       "11  Python, ML, APIs, GenAI, LangChain, LangGraph,...   \n",
+       "14  Python, ML, Pandas, NumPy, Scikit-Learn, GenAI...   \n",
+       "19  Python, ML, NLP, MLOps, Feature Engineering, A...   \n",
+       "20  Python, APIs, LLMs, Prompt Engineering, LangCh...   \n",
+       "22  Python, Javascript, AWS/Azure, VectorDB, LLMs,...   \n",
+       "23  Python, ML, APIs, AWS/Azure, CI/CD, Github, Git,    \n",
+       "29  Python, LangChain, LangGraph, CrewAI, AutoGen,...   \n",
+       "30  Python,  ML, AWS/Azure, SQL, Docker, Kubernete...   \n",
+       "31  Python, APIs, SQL, LLMs, Prompt Engineering, R...   \n",
+       "32                                Python, GenAI, LLMs   \n",
+       "40  Python, Javascript, SQL, LLMs, APIs, VectorDB,...   \n",
+       "42  Python, ML, APIs, LLMs, LangChain, LangGraph, ...   \n",
+       "\n",
+       "                                          soft_skills  \n",
+       "3                      Communication, Problem Solving  \n",
+       "6                      Communication, Problem Solving  \n",
+       "10                     Communication, Problem Solving  \n",
+       "11  Communication, Problem Solving, Analytical Skills  \n",
+       "14                     Communication, Problem Solving  \n",
+       "19                     Communication, Problem Solving  \n",
+       "20                     Communication, Problem Solving  \n",
+       "22                     Communication, Problem Solving  \n",
+       "23                     Communication, Problem Solving  \n",
+       "29                     Communication, Problem Solving  \n",
+       "30                     Communication, Problem Solving  \n",
+       "31                     Communication, Problem Solving  \n",
+       "32                     Communication, Problem Solving  \n",
+       "40                     Communication, Problem Solving  \n",
+       "42                     Communication, Problem Solving  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_senior = df[df['type'].eq('Senior')]\n",
+    "df_senior.head(15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "f9270636",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.057898Z",
+     "iopub.status.busy": "2026-07-05T07:01:36.057507Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.066719Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.065470Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "Index: 70 entries, 3 to 206\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column         Non-Null Count  Dtype\n",
+      "---  ------         --------------  -----\n",
+      " 0   id             70 non-null     int64\n",
+      " 1   role           70 non-null     str  \n",
+      " 2   type           70 non-null     str  \n",
+      " 3   job_desc       70 non-null     str  \n",
+      " 4   year           70 non-null     int64\n",
+      " 5   qualification  70 non-null     str  \n",
+      " 6   experience     70 non-null     str  \n",
+      " 7   tech_skills    70 non-null     str  \n",
+      " 8   soft_skills    70 non-null     str  \n",
+      "dtypes: int64(2), str(7)\n",
+      "memory usage: 5.5 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_senior.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "45322c7e",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.069768Z",
+     "iopub.status.busy": "2026-07-05T07:01:36.069381Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.079081Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.077667Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df_senior.to_csv(r\"C:\\Portfolio-Projects\\Job-Description-Analysis\\data\\clean\\cleaned_job_descriptions_senior.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "c4a8bc2f",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-07-05T07:01:36.081993Z",
+     "iopub.status.busy": "2026-07-05T07:01:36.081606Z",
+     "iopub.status.idle": "2026-07-05T07:01:36.095715Z",
+     "shell.execute_reply": "2026-07-05T07:01:36.094346Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>role</th>\n",
+       "      <th>type</th>\n",
+       "      <th>job_desc</th>\n",
+       "      <th>year</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>experience</th>\n",
+       "      <th>tech_skills</th>\n",
+       "      <th>soft_skills</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>Basic to intermediate Python programming skill...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, GenAI, APIs, Git, Prompt Engineeri...</td>\n",
+       "      <td>Communication, Problem Solving, Analytical Skills</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Strong Python programming\\nExperience with Fas...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Python, React, Javascript, APIs, AWS/Azure, LL...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>24</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>Core Software Engineering (Required)\\nStrong h...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, Javascript, AWS/Azure, VectorDB, LLMs,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>31</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>trong hands-on experience in Python backend de...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, LangChain, LangGraph, CrewAI, AutoGen,...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>32</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>To qualify for the role you must have B.E/ B.T...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Masters</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python,&nbsp;&nbsp;ML, AWS/Azure, SQL, Docker, Kubernete...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>33</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Senior</td>\n",
+       "      <td>• 3–6 years of software development experience...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Not Specified</td>\n",
+       "      <td>5-10</td>\n",
+       "      <td>Python, APIs, SQL, LLMs, Prompt Engineering, R...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>35</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Junior</td>\n",
+       "      <td>Strong foundation in Java, React, NodeJS, Pyth...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0-1</td>\n",
+       "      <td>Java, React, NodeJS, Python, SQL, Excel,&nbsp;&nbsp;Pand...</td>\n",
+       "      <td>Problem Solving, Strong analytical, logical th...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>49</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>1. Building event-driven automations to captur...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, LLMs, ML, APIs, n8n, GenAI</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>50</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>• Currently pursuing a bachelor's or master's ...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, LLMs, GenAI, ML, Agents</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>51</td>\n",
+       "      <td>AI Developer</td>\n",
+       "      <td>Internship</td>\n",
+       "      <td>• Basic knowledge of Python programming.\\n• Un...</td>\n",
+       "      <td>2026</td>\n",
+       "      <td>Bachelors</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Python, ML, GenAI, LLMs, NLP, APIs, TensorFlow...</td>\n",
+       "      <td>Communication, Problem Solving</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    id          role        type  \\\n",
+       "12  13  AI Developer  Internship   \n",
+       "17  18  AI Developer      Junior   \n",
+       "22  24  AI Developer      Senior   \n",
+       "29  31  AI Developer      Senior   \n",
+       "30  32  AI Developer      Senior   \n",
+       "31  33  AI Developer      Senior   \n",
+       "33  35  AI Developer      Junior   \n",
+       "47  49  AI Developer  Internship   \n",
+       "48  50  AI Developer  Internship   \n",
+       "49  51  AI Developer  Internship   \n",
+       "\n",
+       "                                             job_desc  year  qualification  \\\n",
+       "12  Basic to intermediate Python programming skill...  2026      Bachelors   \n",
+       "17  Strong Python programming\\nExperience with Fas...  2026      Bachelors   \n",
+       "22  Core Software Engineering (Required)\\nStrong h...  2026  Not Specified   \n",
+       "29  trong hands-on experience in Python backend de...  2026      Bachelors   \n",
+       "30  To qualify for the role you must have B.E/ B.T...  2026        Masters   \n",
+       "31  • 3–6 years of software development experience...  2026  Not Specified   \n",
+       "33  Strong foundation in Java, React, NodeJS, Pyth...  2026      Bachelors   \n",
+       "47  1. Building event-driven automations to captur...  2026      Bachelors   \n",
+       "48  • Currently pursuing a bachelor's or master's ...  2026      Bachelors   \n",
+       "49  • Basic knowledge of Python programming.\\n• Un...  2026      Bachelors   \n",
+       "\n",
+       "   experience                                        tech_skills  \\\n",
+       "12          0  Python, ML, GenAI, APIs, Git, Prompt Engineeri...   \n",
+       "17        0-1  Python, React, Javascript, APIs, AWS/Azure, LL...   \n",
+       "22       5-10  Python, Javascript, AWS/Azure, VectorDB, LLMs,...   \n",
+       "29       5-10  Python, LangChain, LangGraph, CrewAI, AutoGen,...   \n",
+       "30       5-10  Python,  ML, AWS/Azure, SQL, Docker, Kubernete...   \n",
+       "31       5-10  Python, APIs, SQL, LLMs, Prompt Engineering, R...   \n",
+       "33        0-1  Java, React, NodeJS, Python, SQL, Excel,  Pand...   \n",
+       "47          0                 Python, LLMs, ML, APIs, n8n, GenAI   \n",
+       "48          0                    Python, LLMs, GenAI, ML, Agents   \n",
+       "49          0  Python, ML, GenAI, LLMs, NLP, APIs, TensorFlow...   \n",
+       "\n",
+       "                                          soft_skills  \n",
+       "12  Communication, Problem Solving, Analytical Skills  \n",
+       "17                     Communication, Problem Solving  \n",
+       "22                     Communication, Problem Solving  \n",
+       "29                     Communication, Problem Solving  \n",
+       "30                     Communication, Problem Solving  \n",
+       "31                     Communication, Problem Solving  \n",
+       "33  Problem Solving, Strong analytical, logical th...  \n",
+       "47                     Communication, Problem Solving  \n",
+       "48                     Communication, Problem Solving  \n",
+       "49                     Communication, Problem Solving  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_dev = df[df['role'].eq('AI Developer')]\n",
+    "df_dev.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "26976636",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.14.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

test/test_model.py

@@ -0,0 +1,32 @@
+from __future__ import annotations
+import sys
+from pathlib import Path
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+
+if str(REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(REPO_ROOT))
+
+MODEL_PREP_DIR = REPO_ROOT / "model" / "prep"
+MODEL_OUT_DIR = REPO_ROOT / "model_out"
+
+def test_model_weights_exist():
+    weights_path = MODEL_OUT_DIR / "skill_classifier.pt"
+    assert weights_path.exists(), f"Missing model weights, run pipeline.py: {weights_path}"
+
+
+def test_prepared_data_exist():
+    prepared_data_path = MODEL_PREP_DIR / "prepared_data.npz"
+    assert prepared_data_path.exists(), f"Missing prepared data, run pipeline.py: {prepared_data_path}"
+
+
+def test_label_vocab_exist():
+    vocab_path = MODEL_PREP_DIR / "label_vocab.json"
+    assert vocab_path.exists(), f"Missing label vocab, run pipeline.py: {vocab_path}"
+
+
+def test_vectorizer_exist():
+    vectorizer_path = MODEL_PREP_DIR / "vectorizer.pkl"
+    assert vectorizer_path.exists(), f"Missing vectorizer, run pipeline.py: {vectorizer_path}"
+
+