Employment is the foundation of people's livelihood, and doing a good job in employment guidance for college students plays an important role in ensuring the long-term development of the country. With the rapid development of society, the current employment situation in colleges and universities is more complex and changeable, the employment situation is not optimistic, and the low employment rate has aroused the attention of the society. People also try to solve the problem of difficult employment through campus job fairs, talent markets, online recruitment, and headhunting companies. Realizing precise employment and increasing the employment rate have become the focus of many scholars. Machine learning works by discovering patterns and regularities in data and using these patterns and regularities to make predictions or make decisions. This topic uses machine learning algorithms, according to the characteristics of students and the needs of enterprises, researches and analyzes the relationship between talent training in colleges and universities and student employment, builds a two-way scoring hybrid recommendation model based on content and collaborative filtering algorithms, and builds a machine learning based model based on this model. The employment recommendation platform for college graduates promotes the development of college work. This study solves the problem of project could start through algorithm fusion; proposes a scoring system based on user characteristics and behaviors, solves the problem of sparse scoring matrix of collaborative filtering algorithm, and can be updated dynamically; proposes a two-way scoring strategy to improve the accuracy of hybrid model recommendations and success rate, and realized two-way dynamic recommendation to job seekers and recruiters at the same time. The platform has been built, evaluated and tested in a domestic university, and the platform is running stably. The employment guidance and recommendation system based on machine learning can scientifically and reasonably recommend jobs that match jobs, and at the same time, accurately assign students to recruiting companies, solve the problems of college graduates' employment difficulties and corporate recruitment difficulties, and realize college students' accurate and rapid employment.