Lead Machine Learning Engineer - Video Recommendation-Content Ecosystem - Singapore

About the Team

TikTok content ecosystem team, responsible for designing and optimizing TikTok information delivery and author growth mechanisms to ensure the healthy and sustainable development of the TikTok community. Our work involves optimizing large-scale recommendation algorithms, solving optimization problems with complex constraints, designing and implementing recommendation architectures for various scenarios, and conducting complex and in-depth analysis of product data. Here, you can delve into the improvement and optimization of Machine Learning algorithms, explore cutting-edge technologies; apply algorithms to business through in-depth understanding and thinking of products; and influence the future development direction of products through in-depth analysis of product and content ecology.

Responsibilities

1. Design and develop TikTok’s social recommendation algorithms, building an industry-leading recommendation system to deliver a world-class user experience. 2. Integrate machine learning techniques with various business scenarios (content consumption, social interaction, notifications, following, etc.) to optimize models and strategies, continuously improving recommendation performance. 3. Collaborate closely with product and operations teams to deeply understand user and creator behaviors, and develop targeted algorithm strategies to foster a healthy ecosystem. 4. Research next-generation social recommendation models based on Graph Neural Networks (GNNs) and full-lifecycle user sequence modeling.