Job Prep Heatmap

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Job Prep Heatmap

What Inspired It

Many job seekers, especially students and early-career professionals, struggle to understand how well their skills align with job descriptions. Generic job portals don’t offer feedback on skill gaps, resume quality, or role-fit clarity. We wanted to build something more personalized, intelligent, and actionable — a career tool that doesn’t just list jobs, but guides you to be job-ready.

What I Learned

The importance of resume-to-JD semantic matching using LLMs.
Building user-friendly, responsive UI.
Leveraging Supabase for real-time authentication and role-based user data.
Parsing and analyzing uploaded resumes (PDF/DOCX) to extract relevant content.
Integrating job search APIs and visualizing demand heatmaps for informed decision-making.

How I Built It

Frontend: React + Tailwind CSS for a sleek, modular interface.
Backend: Vite + serverless functions (Bolt.new) to handle resume parsing, skill scoring, and LLM-based insights.
LLM Integration: Hugging Face models for semantic similarity between resume, skills, and job description.(Future Enhacements)
Database: Supabase for user auth, skill tracking, and data persistence.
Deployment: Deployed fully within Bolt.new with custom prompts and UI enhancements.

Challenges We Faced

Parsing resumes reliably across PDF and Word formats.
Matching job descriptions to skills using open-source LLMs in a performant way.(Future Enhacements)
Designing a UI that balances both professional feel and usability.
Making job recommendations meaningful by considering skills, location, and optional resume content.