LinkedIn Job Finder

Upload your resume and instantly find matching LinkedIn job listings. Optionally sign in with LinkedIn to enrich your profile and get better matches.

Live demo: Deploy to Vercel in one click (see below).

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Features

• Resume upload — PDF, DOCX, DOC, TXT (up to 5 MB)
• Automatic skill & role extraction — detects 80+ technical skills and job titles
• LinkedIn job scraping — searches LinkedIn's public jobs guest API
• LinkedIn OAuth sign-in — optional; enriches name/email from your profile
• Rich filters (all optional):
  • Work setting: Remote, Hybrid, On-site
  • Job type: Full-time, Part-time, Contract, Internship, Temporary, Volunteer
  • Experience level: Internship → Executive
  • Date posted: Any time / Past month / Past week / Past 24 hours
  • Sort: Most relevant / Most recent
  • Easy Apply only

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Deploy to Vercel

1. Push this repo to GitHub

git remote add origin https://github.com/<you>/<repo>.git
git push -u origin main

2. Import in Vercel

Go to https://vercel.com/new → Import the repository.

Vercel will auto-detect vercel.json and:

• Build the React frontend with Vite (frontend/dist)
• Deploy the FastAPI backend as a Python serverless function (api/index.py)

3. Add Environment Variables in Vercel

In your Vercel project → Settings → Environment Variables, add:

Variable	Value
LINKEDIN_CLIENT_ID	From your LinkedIn app
LINKEDIN_CLIENT_SECRET	From your LinkedIn app
LINKEDIN_REDIRECT_URI	https://<project>.vercel.app/api/auth/linkedin/callback
FRONTEND_URL	https://<project>.vercel.app

4. LinkedIn App Setup

1. Go to https://www.linkedin.com/developers/apps/new
2. Add redirect URI: https://<project>.vercel.app/api/auth/linkedin/callback
3. Enable scopes: openid, profile, email

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Local Development

# Backend
cd backend
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
cp ../.env.example ../.env    # fill in your credentials
uvicorn main:app --reload --port 8000

# Frontend (new terminal)
cd frontend
npm install
npm run dev        # http://localhost:5173

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Project Structure

Jobs/
├── api/
│   └── index.py              # Vercel serverless entry (imports FastAPI app)
├── backend/
│   ├── main.py               # FastAPI app + all endpoints
│   ├── resume_parser.py      # PDF/DOCX/TXT parsing + skill extraction
│   ├── linkedin_scraper.py   # LinkedIn public jobs scraper + filters
│   ├── linkedin_auth.py      # LinkedIn OAuth 2.0 flow
│   └── requirements.txt
├── frontend/
│   ├── src/
│   │   ├── App.jsx
│   │   └── components/
│   │       ├── JobFilters.jsx     # All search filters UI
│   │       ├── ResumeUpload.jsx
│   │       ├── LinkedInSignIn.jsx
│   │       ├── JobResults.jsx
│   │       └── JobCard.jsx
│   └── package.json
├── vercel.json               # Vercel deployment config
├── requirements.txt          # Root-level (used by Vercel Python runtime)
└── .env.example

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Notes

• LinkedIn may occasionally rate-limit the scraper (HTTP 429). If results are empty, retry after a moment.
• LinkedIn OAuth (Sign in with LinkedIn) enhances the profile display but is optional — the app works without it.
• This project is not affiliated with LinkedIn.