Develop and maintain security policies, standards, and Business Continuity/Disaster Recovery (BCP/DR) plans. Coordinate with IT audits and track security findings to resolution.
Treat the AI-ready data and harness layer as the foundational multiplier for AIDA returns, explicitly designing for build-once, deploy-many reuse across models, agents, channels and BUs.
Follow up on cutting-edge technologies such as global large model inference, GPU high-performance computing, distributed parallelism, and cache optimization, benchmark against mainstream inference frameworks such as vLLM and TensorRT-LLM, complete the implementation of solutions and technological innovation, continuously iterate and optimize the performance and cost advantages of the inference system, and build the core technological barriers of the team.
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.
Lead the implementation and operationalisation of knowledge base and retrieval-augmented generation solution stacks to support scalable GenAI and agentic use cases across business domains.
Participate in intelligent traffic management and large-scale platform development, with exposure to systems managing millions of machines and handling high concurrency. Improve code quality and system reliability through code review, automated testing, observability, and performance optimization.
Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
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.
Implement and enhance knowledge base, retrieval-augmented generation, and memory-store solution components under approved architecture patterns to support scalable Generative AI, Machine Learning, Analytics and Agentic AI use cases.