Summary
Gábor Csapó is a Senior Research Engineer in the San Francisco Bay Area who builds the data systems that power cutting-edge ML research, with a decade of experience spanning production engineering, patent-backed research, and responsible-AI initiatives. At Google he architects end-to-end data flywheels for video, world-model, and avatar research, shipped a data-sampling tool that uniformly improved model metrics by 4%, and led an autonomous multi-agent LLM annotation pipeline that replaced a paid labeling workflow. His work also established fairness and memorization evaluation guardrails that now gate model releases, and he has provisional patents and an ECCV submission in his portfolio. Earlier roles include bringing on-device ML to mass-market Nest products and slashing intraday risk pipeline latency to enable real-time finance operations. He frequently bridges research and product, scaling bespoke research prototypes into production standards, and his background in data visualization and civic-tech projects shows a long-standing interest in making complex systems understandable and impactful.
10 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree, Computer Science, Major GPA: 3.9/4, Bachelor’s Degree, Computer Science, Major GPA: 3.9/4 at New York University Abu Dhabi
High School, Mathematics and Foreign Languages, 5 out of 5, High School, Mathematics and Foreign Languages, 5 out of 5 at Révai Miklós Secondary School
English, German, Hungarian, Chinese