Nathaniel Braun is a senior software engineer with 11 years of experience building large-scale distributed systems, ML infrastructure, and SRE tooling across Google, DeepMind, AWS, Amazon Lab126 and Criteo. He combines deep quantitative training (Caltech, Mines Paris, random modeling) with hands-on engineering—designing training and inference platforms for computer vision and leading teams to deliver production ML services. At Amazon Lab126 he led a seven-engineer team to ship mobile and backend systems for consumer privacy and DL workflows; at Google he now focuses on trust personalization and quality for large language models. Comfortable in Java, TypeScript and Python, he bridges research and production, translating cutting-edge ML requirements into resilient, operable infrastructure. Colleagues describe him as someone who enjoys tackling hard problems collaboratively and whose background in probability and optimization informs pragmatic, data-driven design choices. Based in Tel Aviv, he blends academic rigor with product-minded execution across both cloud-native and embedded-device environments.
10 years of coding experience
15 years of employment as a software developer
Bachelor of Science Mathematics Physics & Computer Science, Bachelor of Science Mathematics Physics & Computer Science at Prépa Stanislas MP*
California Institute of Technology
Master of Science Mathematics & Software Engineering, Master of Science Mathematics & Software Engineering at Mines Paris - PSL
Master of Science (M.Sc.) Random Modeling, Master of Science (M.Sc.) Random Modeling at Université Paris Cité
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Nathaniel Braun - Senior Software Engineer at Google