AI-Assisted CV Evaluation and Optimization for Umjob

Tóm tắt

In the context of increasing demand for digital recruitment solutions, traditional CV screening methods often fall short in delivering accurate and efficient candidate evaluations. This study presents a support system for CV evaluation and optimization, integrated into the UM Jobs website, which utilizes a pre-trained third-party AI model fine-tuned specifically for CV editing. Rather than building custom Machine Learning or Natural Language Processing pipelines, the system adapts an existing AI model through prompt engineering to provide high-quality feedback aligned with job requirements. Key functionalities include relevance analysis between CV content and job descriptions, clarity enhancement suggestions, and personalized recommendations to improve candidate presentation. The development process involved prompt design, system integration, and evaluation using real recruitment scenarios. Results show that the system effectively identifies content weaknesses and offers targeted improvements, helping job seekers increase their chances of success. This solution enhances the digital recruitment process by delivering AI-assisted insights tailored to employer expectations without the need for custom ML/NLP models.