International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 7 Issue 4
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Enhancing Recruitment Efficiency Through AI-Driven Resume Screening and Skill Assessment

Author(s) Dr. Amrita Sarkar, Mr. Sahil Sharma, Mr. Himanshu Himanshu, Mr. Anurag Dey Sarkar, Mr. Aditya Kumar
Country India
Abstract A typical recruitment process in an organization is considered a time-consuming process since many manual steps are involved. Besides this, there also exist biases leading them toward inefficiencies, causing bad candidate-job matches. The present paper articulates the design of Revit-an AI recruitment platform pursuing automation in candidate evaluation and enhancement thereof by NLP and ML techniques. Revit provides a two-step evaluation framework: resume screening using semantic similarity analysis and an auto-generated domain-specific quiz for testing technical skills. The system uses some functionality from spaCy and sentence-transformers, as well as Firebase infrastructure, in order to formalize hiring workflows, minimize human-in-loop decisions, and aid in making data-driven decisions. An empirical evaluation on a data set containing 500 resumes and 50 job postings showed that the system could match candidates against jobs with a 95% accuracy and reduce screening time by 70%. Thus, proving that AI can enhance recruitment processes to achieve scalability, fairness, and transparency.
Keywords AI Recruitment, Resume Screening, Semantic Similarity, Natural Language Processing (NLP), Technical Skill Assessment
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-08-01
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.52621
Short DOI https://doi.org/g9vzk5
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