Architecture for data at the scale of hundreds of billions: Conducting in-depth research and innovation in all aspects, from large-scale offline computing and performance and scheduling optimization of distributed systems to building high-availability, high-throughput, and low-latency online services.
Design and build scalable data flows, data warehouses, scheduling systems, query engines, data services, analytics systems, process standards, and data tools/products to lower the barrier to data usage, ensure stable and efficient system operations, and maximize data value.
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.
Collaborate with data scientists, business analysts, product managers, software engineers and other data engineers to develop, implement and validate deployed data solutions.
Explore and develop a risk-control Agentic AI architecture, including the design and optimization of Skills, long-chain task orchestration, and multi-agent collaborative problem-solving, to improve the efficiency of risk identification and incident resolution.
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.
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.
Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
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.