Machine Learning Engineer Graduate (E-Commerce Recommendation Mall) - 2027 Start (PhD)
Core
Researching and evolving e-commerce recommendation systems using generative AI, LLMs, and agentic architectures to enhance personalization and long-term user value.
Role type
PhD-level research scientist (generative recommendation & LLMs)
Builds
Next-generation generative recommender systems, agentic recommendation architectures, and long-term value modeling algorithms for TikTok's e-commerce platform.
Domain
E-commerce, Generative AI, Large Language Models, Reinforcement Learning
Deliverable
production ML models
Required skills
Generative models, Large Language Models (LLMs), Reinforcement Learning, Recommender systems, Information retrieval, Python, Deep learning frameworks (PyTorch/TensorFlow/JAX), GPU optimization
Preferred skills
Live commerce experience, Generative recommendation, Multimodal foundation models, Causal inference, Long-sequence user behavior modeling, Top-tier conference publications (NeurIPS/ICML/ICLR/KDD/ACL/CVPR/SIGIR/RecSys)
Responsibilities
Drive evolution from discriminative to generative paradigms; leverage LLMs and RL for semantic understanding; build self-evolving agentic recommendation systems; model long-term value and user experience.
Seniority
PhD, Research Scientist
