As a PhD student in our team, you will be at the forefront of developing the next generation of recommendation systems. Your work will be pivotal in enhancing the user experience by delivering more accurate, personalized, and engaging content recommendations. You will have the opportunity to delve into several groundbreaking directions, including but not limited to:
- End-to-End Generative Large Recommendation Systems: We are committed to reimagining the traditional recommendation pipelines. You will explore novel architectures, algorithms, and optimization strategies to break through the limitations of existing systems. By challenging the status quo, you will strive to build more efficient, scalable, and generative recommendation frameworks.
- Ultra-Long Sequence Modeling of User Lifecycle Behavior: Understanding user behavior over an extended period is crucial for providing long-term personalized recommendations. You will focus on modeling the ultra-long sequences of user interactions throughout their lifecycle on TikTok.
- Integrating LLM and Multimodal Technologies for Recommendation: With the abundance of multimodal content (text, image, video, audio) on TikTok, integrating LLM and multimodal technologies into recommendation systems is essential. You will work on leveraging the power of LLMs to understand and process information, and combine it with other multimodal data to enable seamless multimodal-recommendation fusion.
- Posttraining & RL: Exploration of posttraining methods to better align large generative models with business and feed quality needs. Conduct original research on applying RL (e.g., bandit models, policy optimization, offline RL) to recommendation problems (such as diversity & multiobjective fusion problems)
We are looking for talented individuals to join our team in 2026. As a PhD Intern, 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.
We will prioritize candidates who are able to commit to work with the team for 12 weeks. Please state your availability for the internship in your resume.
Applications will be reviewed on a rolling basis. We encourage you to apply early.