Machine Learning Engineer Intern (E-Commerce Recommendation Foundation) - 2027 Start (PhD）
Core
Building shared Recommendation Foundation Models using event-sequence-driven generative paradigms integrating LLMs/VLMs, multimodal understanding, and reinforcement learning.
Role type
PhD intern, research & engineering IC
Builds
Next-generation recommendation systems (retrieval, ranking, end-to-end generative)
Domain
E-commerce, Generative AI, Large Language Models
Deliverable
production ML models
Required skills
Machine learning, Deep learning, LLMs, Generative recommendation, Python, PyTorch
Preferred skills
Pre-training/mid-training/post-training of LLMs, Multimodal semantic tokenization, Top-tier ML/NLP conference publications
Technologies
LLMs, VLMs, PyTorch
Responsibilities
Participate in full training lifecycle of Recommendation Foundation Models; Design and train multimodal semantic tokenizers; Develop LLM-native recommendation; Build next-gen recommendation systems spanning retrieval, ranking, and generative recommendation.
Seniority
PhD Intern, Research & Engineering
