Research on the design and optimization of HR intelligent recruitment system based on machine learning

With the rapid development of artificial intelligence technology, the application of machine learning in various industries has become increasingly deep, in the field of human resources, the traditional recruitment model has low efficiency, matching accuracy is insufficient and other problems, which seriously restricts the talent acquisition and management efficiency of enterprises. In the human resources recruitment link, artificial intelligence liberates the recruitment specialist from the repetitive and redundant preliminary work. The article mainly uses the method of literature survey, briefly introduces the research content and application fields of artificial intelligence in image recognition, machine learning and natural language processing, and designs and optimizes a human resources intelligent recruitment system based on machine learning for this status quo. The system includes core functional modules such as resume parsing and information extraction, accurate matching of jobs and candidates, and interview scoring and decision-making assistance, and utilizes natural language processing (NLP), recommendation algorithms, and deep learning technologies to effectively improve the recruitment efficiency and matching effect. This paper verifies the system performance through experiments and evaluates its optimization effect in terms of recruitment efficiency and accuracy. The system not only can significantly improve the automation level of enterprise recruitment, but also provides important support for intelligent human resource management, which has a broad application prospect.