CareerMatch AI

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  Thumbnail

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  Upload pdf Interface

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  After upload resume analysis

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  Suggestion and requirements for job skills

Inspiration

Finding the right job can be difficult when students and freshers don't know how well their skills match a job description. I built CareerMatch AI to help job seekers understand their strengths, identify missing skills, and plan their next steps toward becoming job-ready.

What It Does

CareerMatch AI is an AI-powered resume and job matching web application. Users upload their resume in PDF format and paste a target job description to receive:

• Resume–job match score with a score breakdown
• Matching skills and missing skills
• Resume improvement suggestions
• Recommended projects to develop relevant skills
• Personalized learning roadmap with actionable steps

The application also provides a demo analysis so users can explore its features without needing an API key.

How I Built It

I built CareerMatch AI as a full-stack web application with a Next.js frontend and a FastAPI backend. The frontend provides the interface for uploading resumes and entering job descriptions, while the backend handles PDF text extraction and analysis.

The application uses AI integration to generate insights from resume content and job requirements. It returns structured results, including match scores, skill gaps, resume suggestions, project recommendations, and a learning roadmap.

I deployed the frontend on Vercel and the backend on Render, making the project accessible online.

Live Demo: https://career-match-ai-lovat.vercel.app/

GitHub Repository: https://github.com/dakshit157/career-match-ai

Challenges I Faced

One of the biggest challenges was deploying the frontend and backend separately and making sure they communicated correctly. I encountered connection errors during deployment and had to check the backend API, endpoint paths, and configuration.

Another challenge was designing the analysis results to be useful and easy to understand instead of simply showing a score. I focused on providing actionable suggestions that help users understand what to improve.

What I Learned

Building CareerMatch AI helped me gain practical experience with full-stack development, API integration, PDF processing, AI-powered analysis, environment configuration, and cloud deployment.

I also learned that building a project involves more than writing code. Testing, debugging, deployment, and making the application useful to real users are equally important.

What's Next

I plan to improve the accuracy and usefulness of the matching results, enhance resume feedback, and add more personalized learning recommendations to help students and freshers prepare for their target roles.

Built With

• ai
• fastapi
• generativeai
• next.js
• python
• react
• render
• resumeanalysis
• vercel