Slava Gurevich is a seasoned systems and platforms software engineer with 13 years of experience building reliable, high-performance infrastructure for large-scale applications. His background spans Ads ML infrastructure at Meta optimizing neural net inference, senior engineering roles at startups, and a decade-plus at Microsoft designing embedded and mobile SDKs with a strong focus on debugging, performance tuning, and AppSec automation. Comfortable across C++, Python, Java and tooling like lldb/windbg, he is language-agnostic and selects the right technology for the problem. He combines hands-on optimization of ML inference pipelines with institutional experience shipping secure, multi-platform software and holds advanced CS training from University of Michigan and coursework at Stanford and Udacity. A practical systems thinker, he brings both deep low-level debugging chops and a track record of embedding security and reliability into the development lifecycle.
13 years of coding experience
19 years of employment as a software developer
MS, Computer and Informational Science, MS, Computer and Informational Science at University of Michigan
Deep Learning, Deep Learning at Coursera
Self-driving car, Self-driving car at Udacity
Computer science, Computer science at Stanford University
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