Responsible for designing, building, and operating scalable data ingestion, transformation, and serving capabilities across a modern hybrid cloud data platform, ensuring solutions are reliable, secure, reusable, and aligned to enterprise architecture and governance standards.
Design and own the evaluation system for LLM Agents, including benchmark construction, LLM-as-Judge with human annotation, and regression/comparison pipelines. Continuously monitor product metrics to guide Agent and model optimization.
Improve the basic search quality and user experience: Optimize query analysis and text relevance matching. Understand e-commerce video content and implement multi-modal matching. Improve users' perception of product authority, and deeply participate in the design and implementation of core search products. Comprehensively improve the end-to-end shopping experience from browsing to after-sales.
Design, develop, and evaluate Agentic AI and multi-agent architectures for task decomposition, planning, reasoning, coordination, and workflow orchestration within the Digital ATCO Assistant project.
Design, develop, and evaluate Agentic AI and multi-agent architectures for task decomposition, planning, reasoning, coordination, and workflow orchestration within the Digital ATCO Assistant project.
Experiment Tracking & Evaluation Reporting: Own MLflow experiment logging for assigned team model runs; conduct model evaluations using standard metrics; produce structured evaluation reports reviewed by team. Your reports directly inform model iteration decisions.
Algorithmic Innovation: Spearhead research into optimal quantization methodologies for advanced low-precision data formats, driving the strategic adoption and expansion of our low-precision computing ecosystem to secure a competitive edge in numerical computing.
Lead the research and development of AI training and inference acceleration algorithms for Agentic AI and Multimodal domains, specifically optimized for next-generation AI compute architectures to maximize compute efficiency and utilization.
Responsible for using algorithms to mine, identify, and predict risks and low-quality merchants, products, and creators in e-commerce scenarios, and assist businesses in managing and controlling them.
Currently pursuing PhD in Computer Science, AI, Mathematics, or a related technical discipline, with a strong foundation in data structures, algorithms, and mathematical modeling.
Develop and deploy data‑driven solutions using manufacturing data (e.g., machine data, quality data, MES/SCADA data) for manufacturing performance improvement