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

What you'll do

• Contribute to the pre-training, mid-training, and post-training lifecycle of Recommendation Foundation Models.
• Design and train multimodal semantic tokenizers for recommendation items.
• Develop LLM-native recommendation and next-generation retrieval, ranking, and end-to-end generative recommendation systems.

What they ask for

• Currently pursuing 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 with pre-training, mid-training, or post-training of LLMs or Foundation Models; or research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization.
• LLM-related publications at top-tier machine learning or natural language processing conferences, or strong achievements in major technical competitions.

Tools

Python, PyTorch, LLMs, VLMs

AI focus

Build Recommendation Foundation Models using LLMs/VLMs, multimodal understanding, reinforcement learning, and generative recommendation; includes multimodal semantic tokenization and LLM training.