Research Scientist Graduate (TikTok Recommendation-Large Recommender Models) - 2026 Start (PhD)
Core
Research and develop large-scale recommender systems to optimize TikTok's personalized content discovery, accuracy, and scalability for billions of users.
Role type
PhD-level Research Scientist (Large-scale Recommender Systems)
Builds
High-performance, scalable recommendation models and systems
Domain
Social Media / Recommendation Systems / Deep Learning
Deliverable
production ML models
Required skills
Deep learning architectures (Transformers, CNNs, RNNs, LSTMs), Large-scale system engineering, Data analysis, Algorithm design, Model lifecycle management (training, fine-tuning, deployment)
Preferred skills
Experience with vast/diverse datasets, Publications in top AI venues (RecSys, NeurIPS, ICML, etc.)
Technologies
Transformers, CNNs, RNNs, LSTMs
Responsibilities
Research and develop large-scale recommender systems; Apply advanced ML/DL techniques to optimize algorithms; Manage end-to-end model lifecycle; Analyze complex data to uncover user preferences; Collaborate with cross-functional teams to implement innovative solutions.
Seniority
PhD, Research Scientist