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.