Summary
Michael Zhang is a Member of Technical Staff at OpenAI with a decade of engineering experience building and researching LLM-driven systems and agent architectures. He blends rigorous CS fundamentals from Stanford (4.03/4.00 undergrad, MS-level work) with hands-on product delivery—driving NIH data integration at Palantir, launching internal LLM tooling at InstaDeep, and shipping an AI agent CRM that won a Pear Pitch prize. Comfortable switching between research and production, he has published technical work in randomized social choice and led teams that measurably improved model performance and platform adoption. Active in the Stanford AI community and fellowships at 8VC and Pear, he mentors peers and scopes high-leverage AI products across venture and campus ecosystems. Notably, he pairs curiosity about AGI with practical impact: accelerating research workflows (40%) and reducing LLM error rates in clinical pipelines. Based in California, he combines a researcher’s attention to prompting and theory with a builder’s track record of deploying AI at scale.
10 years of coding experience
High School Diploma (4.02/4.00), High School Diploma (4.02/4.00) at The Lawrenceville School
Master of Science - MS (4.30/4.00), Management Science and Engineering, Master of Science - MS (4.30/4.00), Management Science and Engineering at Stanford University
English, Chinese, Italian