Machine Learning Engineer Graduate (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-level Research Scientist / Machine Learning Engineer (Generative Recommendation)
Builds
Next-generation recommendation systems (retrieval, ranking, end-to-end generative) powered by foundation models
Domain
E-commerce, Large Language Models, Multimodal AI, Generative AI
Deliverable
production ML models
Required skills
PhD in CS/EE/Math/Statistics, Machine Learning, Deep Learning, LLMs, Generative Recommendation, Python, PyTorch
Preferred skills
Pre-training/Mid-training/Post-training of LLMs, Multimodal semantic tokenization, Publications at NeurIPS/ICML/ICLR/ACL/EMNLP/NAACL, Technical competitions
Technologies
PyTorch, LLMs, VLMs, Reinforcement Learning
Responsibilities
Participate in full training lifecycle of Recommendation Foundation Models (pre/mid/post-training), Design and train multimodal semantic tokenizers, Develop LLM-native recommendation, Build next-gen recommendation systems spanning retrieval, ranking, and generative recommendation
Seniority
PhD, Research & Engineering