Large Recommend Model Algorithm Engineer - Global E-Commerce

nt agents.
We value original exploration and encourage both research thinking and engineering excellence. Every team member is empowered to propose hypotheses and validate ideas in an open environment - your code and papers may help define the next paradigm of recommendation systems. We seek individuals with a general intelligence mindset to join us in redefining the future of recommendation.

Responsibilities
Build and optimize cross-scenario shared Foundation Models to enable unified modeling and efficient inference.
Advance the event-sequence-driven generative recommendation paradigm, integrating multimodal understanding and generative capabilities.
Apply LLM technologies across retrieval, ranking, and re-ranking stages; participate in model training, inference optimization, and system co-design.
Explore the integration of LLMs / VLMs with recommendation systems to develop adaptive and evolving intelligent recommenders.
Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience.

Qualifications

Minimum Qualifications

• Solid theoretical foundation in machine learning, deep learning, or information retrieval.
• Proficiency in Python and familiarity with mainstream deep learning frameworks (e.g., PyTorch).
• Strong passion for intelligent recommendation systems and a self-driven research mindset.

Preferred Qualifications

• Experience in large-scale recommendation system development or large-model training, with notable technical achievements in a sub-area.
• Research experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation.
• Familiarity with pre-training and post-training processes for large language models (LLMs) or Foundation Models.