Summary
Osman Kilinc is a software engineer based in San Francisco with eight years of experience building high-performance data and embedded systems, currently focusing on vehicle data infrastructure and lossless logging at Zoox. He holds an MS in Machine Learning and Data Science from UCSD and brings research-led expertise in decentralized and continual learning from his graduate work on peer-to-peer training and neural network watermarking. Osman has shipped production-grade systems across robotics, semiconductor tooling, medical devices, and web apps—designing CI pipelines, simulation/test harnesses, and real-time data pipelines that scale to tough environmental constraints. Comfortable across C++, C#, and modern software stacks, he bridges research and engineering to turn novel ML ideas into robust, testable deployments. An often-overlooked strength is his track record of improving real-time signal processing and data throughput (e.g., a 20x rendering speedup via an OpenGL plotting library), which informs his pragmatic approach to high-bandwidth logging and on-vehicle software.
9 years of coding experience
5 years of employment as a software developer
University of California, San Diego
Bachelor’s Degree, Computer Engineering, Bachelor’s Degree, Computer Engineering at Istanbul Technical University
English, Turkish