Research Scientist Graduate (TikTok Recommendation-Post-Training) - 2026 Start (PhD)

Our team’s mission is to empower recommender systems with reasoning and planning capabilities, enabling them to move beyond surface-level personalization and foster long-term user growth, satisfaction, and trust. This mission is supported by ongoing research and the practical application of multimodal large language models, reinforcement learning, uncertainty estimation, and alignment. As a pioneer in the field, we are committed to producing groundbreaking research that advances both academic understanding and real-world deployment, helping to shape the future of intelligent recommendation systems. If you are excited about working at the frontier of applied research with real product impact-and contributing to a high-caliber, collaborative, and curious team-we'd love to hear from you.



We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.



Successful candidates must be able to commit to an onboarding date by end of year 2026.



We will prioritize candidates who are able to commit to these start dates. Please state your availability and graduation date clearly in your resume.



Applications will be reviewed on a rolling basis. We encourage you to apply early.



Responsibilities

- Driving research on generative recommendation models with reasoning and planning capabilities to foster long-term objectives

- Following SoTA progress in relevant fields and identifying valuable ideas for implementation

- Generative recommendation model development, training, deployment, and maintenance