Danila Sinopalnikov
Software Engineer at Google
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolDanila Sinopalnikov is a seasoned software engineer with 12+ years of experience, currently based in Zurich and working at Google. He combines deep theoretical grounding—a Master's in Computational Complexity from Saint Petersburg State University—with extensive systems and back-end engineering experience dating back to Sun Microsystems and Elbrus/MCST. At Google he contributes to scalable production systems and has also applied his skills to open-source ML tooling, notably enhancing DeepMind's Acme library with a JAX distributional module and a MultivariateNormalDiagHead. His work spans low-level refactors, batching and environment orchestration fixes, and pragmatic feature development that bridges research code and production needs. Colleagues rely on him for thoughtful, correctness-first engineering that balances mathematical rigor with deployable implementations. An uncommon blend of formal CS training and decades of industry practice makes him effective at turning complex algorithms into robust infrastructure.
12 years of coding experience
12 years of employment as a software developer
Master's Degree, Computational Complexity, Master's Degree, Computational Complexity at Saint Petersburg State University
Github Skills (10)
machine-learning10
jax10
python10
tensorflow-probability10
reinforcement-learning10
haiku9
data-structure7
data-structures7
algorithm7
algorithms7
Programming languages (5)
Github contributions (5)
google-deepmind/acme
Oct 2020 - Nov 2022
A library of reinforcement learning components and agents
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:5 reviews, 132 commits, 1 PR in 2 years 1 month
Contributions summary:Danila implemented new features and made improvements to the Acme reinforcement learning library. Their work involved developing a distributional module for JAX, contributing to the creation of a MultivariateNormalDiagHead, and refactoring the codebase. They also addressed issues with batch concatenation in JAX utils and moved environment creation to a helper library.
reinforcement-learningreinforcementagentsdeep-reinforcement-learning
fbkinfo/rosvybory
Aug 2013 - Sep 2013
Contributions:10 commits in 8 days
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