Research Scientist Intern (TikTok Recommendation-LLMs, RL, GenAI) - 2026 Start (PhD)
Core
Researching next-generation recommendation systems using LLMs, reinforcement learning, and generative AI to enhance content discovery for hundreds of millions of users.
Role type
PhD Research Intern (Recommendation Systems, GenAI, RL)
Builds
End-to-end generative recommendation frameworks, ultra-long sequence user behavior models, and multimodal recommendation systems.
Domain
Social Media, Recommendation Systems, Generative AI, Reinforcement Learning
Deliverable
research
Required skills
Python, PyTorch/TensorFlow, Large-scale ML, Data Structures & Algorithms, Statistical Modeling
Preferred skills
First-author publications in top-tier conferences, Experience with LLMs/Multimodal models, Reinforcement Learning/Bandit algorithms, Large-scale system experience
Technologies
PyTorch, TensorFlow, LLMs, Bandit models, Offline RL
Responsibilities
Design and implement innovative algorithms for recommendation performance, Analyze large-scale user behavior and content data, Deploy and evaluate recommendation systems in real-world scenarios, Collaborate with cross-disciplinary teams on advanced systems
Seniority
Intern, Research
