Machine Learning Engineer Graduate (E-Commerce Recommendation Foundation)- 2027 Start (PhD)

What you'll do

• Participate in pre-training, mid-training, and post-training of Recommendation Foundation Models.
• Design and train multimodal semantic tokenizers that encode item content into discrete tokens.
• Build LLM-native and generative recommendation systems across retrieval, ranking, and end-to-end recommendation.

What they ask for

• Completing or recently completed a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
• Solid foundation in machine learning and deep learning, with strong interest in LLMs and generative recommendation.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch.
• Self-driven, with a strong research mindset and solid engineering skills.

Nice to have

• Experience training LLMs or Foundation Models, or research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization.
• LLM-related publications at listed top-tier conferences or strong achievements in major technical competitions.

Tools

Python, PyTorch, LLMs, VLMs

AI focus

Research and engineering for Recommendation Foundation Models, including LLM/VLM integration, multimodal semantic tokenization, reinforcement learning, and generative recommendation.