AI/ML Engineer and Researcher
Experience
Recent work in scientific AI, large language model systems, and production software engineering.
UC San Diego
Researching agentic systems for weather science, including execution environments and tool APIs that let language models write code, run analyses, inspect intermediate outputs, and revise solutions through iterative reasoning.
Built evaluation and synthetic-task pipelines that turn meteorological narratives into executable, verifiable benchmarks for scientific agents.
Tencent AI Lab
Developed a real-time, multi-stage LLM pipeline for Honor of Kings battle reporting, covering event extraction, narrative planning, grounded generation, and time-aware commentary.
Used GraphRAG, retrieval, and model distillation to improve factual grounding while reducing inference cost under production latency constraints.
Ai4C Applied Research Institute
Built and maintained a customer-facing platform with a headless backend, GraphQL gateway, and React frontend, deployed through Docker, GitHub Actions, and Kubernetes.
Developed an internal LLM assistant for proposal drafting using prompt templates, lightweight memory, and retrieval over client-specific context.