Participate in the exploration and development of personalized AI search, with a focus on harness engineering, post-training optimization, and rubric-based automated evaluation, to build next-generation search experiences that better understand users, reason over intent, and make intelligent decisions.
Next-Gen Marketing Tech: Go beyond traditional discriminative uplift prediction. Research and productionize cutting-edge causal inference and AI technologies — including Uplift Modeling, E2E Modeling, RL, LLMs, and AI Agents — to directly address user conversion and repeat purchase behavior.
Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.