AI-Driven Resume–Job Description Matching System

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  User interface for uploading resumes and entering job descriptions

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  AI-generated match score and skill analysis using Gemini

Inspiration

Recruiters and applicants often struggle with resume screening because traditional keyword matching misses context and true skill relevance. I wanted to build a smarter system that understands meaning, not just words.

What it does

This project is an AI-driven Resume–Job Description Matching System that compares resumes with job descriptions using Gemini. It generates a match score, highlights relevant skills, and identifies gaps to help both recruiters and candidates make better decisions.

How I built it

The system uses Gemini to perform semantic analysis between resume content and job descriptions. The frontend allows users to upload resumes and paste job descriptions, while the backend processes the data, sends structured prompts to Gemini, and returns similarity insights and scores.

Challenges I ran into

Handling varied resume formats and ensuring consistent AI output was challenging. Prompt design and response parsing required careful iteration to achieve reliable and explainable results within hackathon constraints.

Accomplishments that I'm proud of

I successfully built an end-to-end working prototype that demonstrates real-world hiring use cases. Integrating Gemini effectively within a limited time and producing meaningful insights was a major win.

What I learned

I learned how to design effective prompts for Gemini, handle AI-generated responses safely, and structure an AI-powered system for real-world applications under time pressure.

What's next

Future improvements include ATS integration, multi-resume comparison, bias reduction strategies, and enhanced scoring explanations.

Built With

• css
• express.js
• gemini
• google-ai
• javascript
• node.js
• react