Tech Lead Research Scientist - Recommendation Foundation Models (Global E-commerce)

What you'll do

• Define and lead foundation-model strategy, training, evaluation, and deployment.
• Advance event-sequence-driven generative recommendation and multimodal representations for retrieval, ranking, and user-intent modeling.
• Lead technical execution, experiments, cross-functional collaboration, and colleague mentorship.

What they ask for

• MS/PhD in Computer Science or a related technical field, or equivalent industrial research experience.
• Demonstrated LLM impact in industry or academia, or experience building and deploying large-scale generative recommendation systems.
• Strong machine learning and deep learning fundamentals, with expertise in LLMs, foundation models, or generative recommendation.
• Ability to lead complex technical work from problem definition through evaluation and deployment, and collaborate across research and engineering.

Nice to have

• Experience setting research roadmaps, leading shared modeling platforms or cross-team initiatives, and mentoring researchers and engineers.
• Experience with foundation-model training or post-training, reinforcement learning, preference optimization, or related areas listed in the posting.

Tools

LLMs, VLMs, reinforcement learning

AI focus

Develop and deploy LLM-native, event-sequence-driven generative recommendation foundation models, multimodal representations, and recommendation agents; evaluate quality, long-term user value, latency, and inference cost.