Smart HR Management System: Job Posting, Screening & Decision Support

Traditional recruitment involves several manual steps that often slow down the hiring process and lead to inconsistencies, especially when organisations deal with a large number of applicants. Tasks such as creating job descriptions, advertising vacancies on different platforms, and manually reviewing resumes can become overwhelming, resulting in delays and varying quality in decision-making. To address these issues, this study introduces an AI-driven Smart HR Management System designed to streamline the recruitment workflow. The system integrates Natural Language Processing (NLP) and Machine Learning (ML) techniques to convert unstructured job and resume information into structured, meaningful data. GPT-based language models assist in generating clear and standardised job descriptions, while TF- IDF and Cosine Similarity methods help measure the alignment between job requirements and candidate profiles. The proposed solution aims to reduce the time required to fill positions, maintain uniformity across job postings, minimise reliance on subjective judgement, and assist HR teams with transparent and evidence-based insights through visually rich dashboards.