The recruitment is a crucial factor in the development and achievement of an organization. Nevertheless, the conventional resume screening approaches are ineffective, time consuming and subject to biasness. Being AI-based, the Smart Resume Screening and Matching System described in this paper automates the processes of resumes parsing, matching with job-candidates, and ranking through the application of Natural Language Processing (NLP) and machine learning algorithms. The system picks out the structured information of unstructured resumes, matches them with job descriptions and generates compatibility scores. It tries to make the recruitment more efficient, less human, and fairer when assessing the candidates. The system makes use of Python-based structures, and NLP extractors spaCy and NLTK to extract and compute similarities. Findings show a high degree of screening accuracy and speed compared to manual methods, and provides scalable and objective recruitment solution.