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

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 recommendation item content into discrete tokens.
• Build recommendation 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.
• Research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization; relevant publications or major technical competition achievements.

Tools

Python, PyTorch, LLMs, VLMs

AI focus

Develop Recommendation Foundation Models and generative recommendation by integrating LLMs/VLMs, multimodal understanding, and reinforcement learning; train multimodal semantic tokenizers and incorporate recommendation tasks into LLM training.