Authors : Karmesh Meritia; Vishal Ghosh; Dr. P. S. Thanigaivelu

Volume/Issue : Volume 10 - 2025, Issue 5 - May

Google Scholar : https://tinyurl.com/26bzry46

Scribd : https://tinyurl.com/yxf258ty

DOI : https://doi.org/10.38124/ijisrt/25may452

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This research presents an AI-powered web system designed to streamline the job application process, particularly for fresh graduates struggling to tailor resumes to specific job descriptions. By integrating NLP models and external APIs, the system offers personalized recommendations, evaluates resume-job fit, suggests roles, generates tailored drafts, and recommends real-time job postings via the Adzuna API. Leveraging the all-MiniLM-L6-v2 sentence transformer for role recommendations and Google's Gemini for JD-specific resume enhancements, it dynamically aligns candidate profiles with job expectations, moving beyond traditional heuristic-based tools. Utilizing datasets from Kaggle and LinkedIn, this system aims to provide practical, real-time improvements, demonstrating AI’s potential to optimize job searches and enhance employment prospects.

Keywords : Resume Enhancement, Job Description Matching, AI-Powered Resume Builder, NLP in Job Search, Sentence Transformers, Cosine Similarity, Resume Optimization, AI in Recruitment, Job Role Recommendation, Live Job Posting.

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