Machine Learning Engineer, TikTok Content Recommendation (Ecosystem & Cold-Start)

About the Team Our team is responsible for designing and optimizing TikTok s content distribution and author growth mechanism to ensure the healthy and sustainable development of TikTok s content ecosystem. 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 analyses of product data. Here, you can drive deeper into the improvement and optimization of machine learning/deep learning algorithms, including but not limited to Mathematics, CV/NLP technology, multi-task learning, multi-modal technology, meta-learning, reinforcement learning, causal inference, metric learning, graph neural networks, active learning, life long learning, etc.

Responsibilities - What You II Do

• Build industry-leading recommendation system, improving user experience, the content ecosystem and platform security;
• Deliver end-to-end machine learning solution to address critical product challenges;
• Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.
• Work with cross functional teams to design product strategies and build solutions to grow TikTok in important markets. Minimum Qualifications
• Bachelor degree or above in computer science or a related major, with 2+ years of related work experience;
• Strong software development experience with C++, Python or other programming language;
• Experience in one or more of the following areas: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product;
• Strong communication and teamwork skills;
• Passion about techniques and solving challenging problems.