AI Powered Recruitment System

Abstract

The recruitment process in many organizations involves reviewing a large number of resumes to identify suitable candidates for job positions. This manual screening process is time-consuming, labor-intensive, and often prone to human bias, making it difficult for recruiters to efficiently evaluate all applications. To address these challenges, this study proposes an AI-powered automated resume screening and interview system that utilizes advanced machine learning and natural language processing techniques to analyze resumes and assist in the recruitment process. The system is designed to automatically extract relevant information such as skills, qualifications, work experience, and keywords from candidate resumes and match them with job requirements to determine the suitability of applicants.The proposed system incorporates multiple machine learning and artificial intelligence approaches, including text preprocessing, feature extraction, and classification algorithms to evaluate candidate profiles. Natural Language Processing (NLP) techniques are used to process and interpret textual information present in resumes, while machine learning models analyze the extracted features to classify and rank candidates based on their compatibility with the job description. Additionally, the system includes an automated interview module that generates relevant interview questions and evaluates candidate responses, further assisting recruiters in shortlisting qualified applicants.By integrating artificial intelligence with recruitment processes, the proposed system aims to significantly reduce the time and effort required for resume screening while improving the accuracy and fairness of candidate selection. The automated evaluation and ranking mechanism helps recruiters identify the most suitable candidates efficiently and supports data-driven decision-making in hiring processes. The implementation of such an intelligent recruitment system has the potential to streamline hiring workflows, minimize human bias, and enhance the overall efficiency of talent acquisition in modern organizations.