Role OverviewJoin the Recommendation Foundation team to build shared Recommendation Foundation Models across scenarios, exploring event-sequence-driven generative recommendation paradigms that integrate large language and vision-language models. Contribute to advancing recommendation systems beyond click prediction toward general-purpose recommendation agents.
What You Will Do
Participate in the full training lifecycle of Recommendation Foundation Models, design and train multimodal semantic tokenizers, develop LLM-native recommendation, and build the next generation of recommendation systems powered by Recommendation Foundation Models.
Why It Might Be a Fit
We value original exploration and encourage research thinking and engineering practice equally. Every team member can propose hypotheses and validate ideas in an open environment. Opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Requirements
- Individuals who are completing or have 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.
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