Job Description: Enhance existing recall, pre-ranking, ranking, re-ranking modules in our large scale ads platform, and continuously improve ads quality. Iterate ads core models, including but not limited to CTR/CVR, expand and optimize feature set, search and create new model architecture. Optimize ads bidding, deduction and traffic allocation strategies to create better ads bidding mechanism and increase ads monetisation efficiency. Focus on the research of search, recommendation and ads to apply relevant strategies and adapt to our platform for implementation in our production system. Requirements: Bachelor's Degree or above in Computer Science or a related field, graduating from December 2025 to May 2026. Deep understanding in machine learning and deep learning theory, publications in machine learning and data mining or related conferences is a bonus. Sensitive to data and business, passionate about technical challenges, have excellent critical thinking skills. Be familiar with big data processing tools, have experience with one or more of the following tools: Hadoop, Spark, Hive and Flink etc. Effective team player and has good communication skills. Proactive and self-motivated. Preferred to have Ads algorithm internship experience.