1. Algorithm Model Development and Optimization: Design, develop, and deploy machine learning models and algorithms, optimizing and improving the algorithm models to enhance performance and accuracy;

2. Data Processing and Feature Engineering: Conduct data cleaning, preprocessing, and feature engineering to ensure data quality;

3. Algorithm Performance Evaluation: Design and execute experiments to assess model performance, using appropriate evaluation metrics and methods to validate model effectiveness;

4. Technical Research and Innovation: Stay updated with the latest research findings and technological trends in machine learning, proposing and implementing algorithmic solutions;

5. Cross-Departmental Collaboration: Work closely with team members to understand business requirements and translate them into technical implementations.

1. Bachelor's degree or above in Computer Science, Statistics, Mathematics, or related fields;

2. Familiarity with mainstream machine learning/deep learning frameworks, with proficiency in at least one programming language among Python, Java, or C++;

3. Experience in recommendation system projects, capable of independently completing the entire process from data processing to model deployment;

4. Experience in NLP, visual analysis, or graph algorithms will be considered a plus;

5. Strong communication skills, teamwork spirit, and learning ability;

6. Familiarity with Flink is preferred.