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

What you'll do

• Participate in recommendation foundation model pre-training, mid-training, and post-training.
• Design and train multimodal semantic tokenizers to encode recommendation item content.
• Develop LLM-native recommendation and systems spanning retrieval, ranking, and end-to-end generative recommendation.

What they ask for

• Completing or recently completed a Bachelor's degree 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 relevant generative recommendation, LLM-native recommendation, or multimodal semantic tokenization projects.
• LLM-related publications at named top-tier conferences or strong achievements in major technical competitions.

Tools

Python, PyTorch, LLMs, VLMs

AI focus

Develop Recommendation Foundation Models and generative recommendation using LLMs/VLMs, multimodal understanding, reinforcement learning, and semantic tokenization.