Ai Powered Recruitment Management System

Student: OLIVER AYUBA (Project, 2025)
Department of Computer Science
Modibbo Adama University, Yola, Adamawa State

Abstract

ABSTRACT This project addressed the challenges of inefficiency and inherent human bias in traditional recruitment processes by designing and implementing an AI-powered Recruitment Management System (RMS). The system leverages Natural Language Processing (NLP) to automatically parse and extract key information from unstructured CVs, and a machine learning pipeline utilizing Sentence-BERT and a Random Forest algorithm to accurately match and rank candidates to job vacancies. A critical component of the system is the integration of the IBM AI Fairness 360 toolkit for real-time algorithmic bias detection, ensuring the system promotes fairness and equity. The evaluation of the system's performance, as detailed in the project report, demonstrates its effectiveness in providing accurate candidate rankings and its viability as a powerful, data-driven decision-support tool for recruiters. The final conclusion affirms that the developed RMS offers a more efficient, transparent, and ethical alternative to conventional hiring methods.

Keywords
AI recruitment CV parsing machine learning natural language processing candidate ranking job matching algorithmic fairness IBM AI Fairness 360 Django web app automated hiring
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