The employability of undergraduate students in private colleges and universities holds paramount significance in the ever-evolving landscape of higher education. This research endeavors to address this critical concern by proposing an innovative approach—leveraging reinforcement learning and optimization modeling—to enhance employability among undergraduate students in Guangxi private institutions of higher education. The study commences with a comprehensive review of the literature, shedding light on the current state of employability enhancement strategies, the pivotal role of reinforcement learning in educational contexts, and the applicability of optimization models to address the complexities of employability development. Through this review, we identify a notable research gap in the intersection of these domains. Our methodology entails the collection and analysis of relevant data to construct an optimization model designed to optimize employability-enhancing interventions. Employing reinforcement learning algorithms, we dynamically adapt strategies to individual student needs, considering academic performance, skills acquisition, and career aspirations. The model's flexibility and adaptability align with the diverse and dynamic nature of the student population within private institutions. The results of our study demonstrate the effectiveness of the proposed model in enhancing employability outcomes. By tailoring interventions to each student's unique journey, we observed significant improvements in academic achievement, skills development, and career readiness. These findings underscore the potential of reinforcement learning and optimization modeling as valuable tools for employability enhancement in higher education. In conclusion, this research contributes to the field of education by offering a novel framework for employability enhancement in the context of private colleges and universities in Guangxi. The application of reinforcement learning, and optimization models not only enriches our understanding of student development but also offers practical insights for educators, policymakers, and institutions seeking to prepare students for the dynamic demands of the modern workforce.