Tian Lan is a software engineer and machine learning scientist with 8 years of experience building production-grade ML systems, from GenAI and scalable reinforcement learning to CRM recommendation engines and high-frequency trading infrastructure. Currently at Google, Tian develops data infrastructure and analytics tools for GenAI, following a technical lead role at Salesforce A.I. Research where he shipped agentic generative models (xLAM/Agentforce), led AI Ops for real-time cloud protection, and contributed to popular OSS projects like Merlion and warp-drive. He combines rigorous academic training (PhD in Applied Physics from Caltech) with hands-on full-stack delivery—designing backends, frontends, CI/CD, and high-throughput CPU engines for simulation and trading. Tian has published first-author papers in venues including Nature Communications, JACS, JMLR and ICLR, reflecting a rare blend of research depth and product impact. He has led cross-continental teams and built AI platforms from zero that materially boosted business metrics and contributed to a major $500M acquisition. Colleagues would note his ability to translate complex physics-grade modeling into scalable, maintainable production systems.
8 years of coding experience
8 years of employment as a software developer
Bachelor's degree Physics (Kuang YM Honors Program), Bachelor's degree Physics (Kuang YM Honors Program) at Nanjing University
California Institute of Technology
High School Diploma, High School Diploma at 南京师范大学附中
Contributions:10 PRs, 12 pushes, 5 branches in 11 days
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