International Journal of Advanced Research in Computer and Communication Engineering

Abstract: This paper presents an AI-Based Recruitment Preparation System that transforms traditional hiring pro- cesses through intelligent automation and machine learning. The platform integrates Natural Language Pro- cessing (NLP), emotion recognition, and automated coding evaluation to provide comprehensive candidate assessment. Built on a microservices architecture, the system offers resume analysis with semantic matching achieving 85% accuracy, dynamic interview question generation, real-time emotion analysis using DeepFace, and automated coding assessment via Judge0 API. The solution addresses critical challenges in recruitment including manual evaluation overhead, limited candidate feedback, and skill-job mismatches. Deployed using Docker and Kubernetes with CI/CD automation, the system demonstrates 86% test pass rate and sub-500ms API response times. This research contributes a production-ready platform that reduces hiring cycle time by 80% while maintaining consistency and eliminating bias through automated evaluation pipelines.

Keywords: Artificial Intelligence, Natural Language Processing, Recruitment Automation, Emotion Recognition, Microservices Architecture, Machine Learning, Interview Assessment, Resume Analysis.

Downloads: | DOI: 10.17148/IJARCCE.2025.141025