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Resume Job Matcher

Developed an AI-powered Resume Job Matcher that analyzes resumes against job descriptions using NLP and semantic similarity techniques to generate match scores, identify missing skills, and provide ATS-focused optimization recommendations. Built a scalable full-stack application for automated resume evaluation and personalized job application insights.

Resume Job Matcher

Overview

Resume Job Matcher is an AI-powered web application that helps job seekers evaluate how well their resumes match specific job descriptions. The platform analyzes resumes and job postings using Natural Language Processing (NLP), semantic similarity, and keyword matching techniques to generate an overall match score. It identifies missing skills, highlights strengths, and provides personalized recommendations to improve ATS compatibility and job application success rates. The system features a user-friendly interface for uploading resumes and viewing detailed insights in real time. By combining AI-driven text analysis with a scalable full-stack architecture, the project streamlines resume optimization and helps candidates target roles more effectively.

Key Achievements

Developed an AI-powered resume evaluation platform that automates resume-to-job matching and ATS compatibility analysis
Implemented semantic similarity scoring and skill extraction pipelines to generate personalized job-fit assessments
Built an end-to-end system for resume parsing, job description analysis, and actionable resume optimization recommendations
Leveraged NLP and embedding-based models to identify qualification gaps and improve candidate-job matching accuracy

Tech Stack

React.jsNode.jsExpress.jsPythonSentence TransformersHugging Facescikit-learnPostgreSQLDockerGitHub ActionsTailwind CSSREST APIs

Hruthi Muggalla

Software Engineer based in Georgia. MS Computer Science at University of Georgia. Building full-stack applications and decentralized systems.

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