Author
Listed:
- Akash Ashok Phadtare
- Abhijit Sanjay Thorat
- Ganesh Motiram Jadhav
- Shubham Dattatray Jadhav
- Shrikant Nagnath Kadam
- Bere S. S
- Jagtap P.S
Abstract
In the modern recruitment landscape, job seekers often struggle to create professional and Applicant Tracking System (ATS)-compliant resumes while simultaneously identifying relevant job opportunities. Many qualified candidates fail to pass ATS filters or are overlooked due to unoptimized resumes and inefficient job searches. This project, AI-Powered Resume Builder and Job Recommender System, integrates Generative Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML) to automate resume creation, analysis, and job matching. The proposed system consists of three modules: (1) Resume Builder, which uses Generative AI (via Gemini API) to automatically generate professional resumes; (2) Resume Analyzer, which applies NLP and ML algorithms to evaluate and enhance resume quality through ATS scoring and improvement suggestions; and (3) Job Recommender, which retrieves and ranks suitable job listings using semantic similarity and API-based data integration. This intelligent system reduces the manual effort involved in resume preparation and job searching, ensures ATS optimization, and provides personalized job recommendations. It thus bridges the gap between job seekers and recruiters by enhancing visibility, efficiency, and hiring potential through AI-driven automation.
Suggested Citation
Akash Ashok Phadtare & Abhijit Sanjay Thorat & Ganesh Motiram Jadhav & Shubham Dattatray Jadhav & Shrikant Nagnath Kadam & Bere S. S & Jagtap P.S, 2026.
"AI Powered Resume Builder and Analyzer,"
International Journal of Scientific Research in Artificial Intelligence and Machine Learning, International Journal of Scientific Research in Artificial Intelligence and Machine Learning, vol. 2(3), pages 74-83, May.
Handle:
RePEc:jbo:ijsrml:v2:y2026:i3:id:60
Note: Article URL: https://ijsraiml.com/home/article/view/IJSRAIML26241
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