AI-Powered Resume Screening and Role-Fit Analysis System

This study presents an advanced AI-driven Resume Screening and RoleFit System designed to automate and optimize

the recruitment process. The proposed framework integrates Large Language Models (LLMs), the OpenAI API, and Machine

Learning algorithms within a Python Flask environment to analyze and classify multiple resumes simultaneously. The system

performs intelligent parsing, skill extraction, and role matching to evaluate candidate suitability for various job positions. It

leverages a custom scoring algorithm to assign quantitative rankings, organizing candidates from top to bottom based on their

qualifications, experience, and skill relevance. Additionally, the system categorizes applicants into roles such as frontend,

backend, or full-stack according to detected technical proficiencies. By combining automated resume analysis with AI-based

decision support, the framework ensures faster, unbiased, and more efficient candidate shortlisting, significantly reducing

manual effort and improving hiring accuracy for recruiters and organizations.