Avital Oliver
Neural Network Plumber at I can't even begin to count how many side projects
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAvital Oliver is a software engineer and researcher with roughly two decades of experience spanning embedded systems, full-stack web frameworks, and state-of-the-art deep learning. Currently a "Neural Network Plumber" at OpenAI, he previously led Flax at Google Brain—helping grow it into the dominant JAX neural-network library used across major models and MLPerf-winning projects. He focuses on ergonomic API design and scalable, memory- and compute-efficient techniques for very large vision models, with publications and contributions to influential repos like google/flax and openai/universe-starter-agent. A longtime open-source contributor and systems builder, he helped ship core pieces of Meteor and production-ready realtime frameworks like ShareDB and Luna2. Beyond engineering, he runs The Global Math Circle and has a strong mathematical foundation (MSc in Math & CS), which he applies to principled model and API design. Notably, his career began with experimental low-level projects (e.g., a 3D engine in x86 assembly), reflecting a rare blend of deep systems intuition and ML research.
17 years of coding experience
14 years of employment as a software developer
M.Sc., Mathematics and Computer Science, M.Sc., Mathematics and Computer Science at Bar-Ilan UniversityVisiting Student, Mathematics, Visiting Student, Mathematics at Rutgers University
English, Hebrew
Stackoverflow
1,542reputation
46kreached
15answers
0questions
meteor
top-5%
Github Skills (31)
operational-transformation10
javascript10
back-end-development10
python10
testing10
machine-learning10
flax10
operational-transform10
neural-network10
transform10
jax10
backend10
meteor10
react10
unsupervised-learning9
Programming languages (9)
Github contributions (5)
google/flax
Jan 2020 - Feb 2022
Flax is a neural network library for JAX that is designed for flexibility.
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 337 reviews, 238 commits in 2 years 1 month
Contributions summary:Avital's contributions primarily focused on the development and improvement of machine learning components within the Flax framework. Their work included modifying the dropout implementation, fixing issues related to random number generation (RNG) streams in dropout, and refining examples, such as the LM1B example pipeline. They introduced new features like adding a dtype argument to `DenseGeneral`, weight normalization, and group normalization layers, along with improving the Module class methods. The user also added a momentum contrast for unsupervised visual representation learning.
jaxneural-network
share/sharedb
Mar 2016 - Sep 2016
Realtime database backend based on Operational Transformation (OT)
Role in this project:Back-end Developer
Back-end DeveloperContributions:73 commits, 23 PRs, 46 pushes in 6 months
Contributions summary:Avital primarily focused on improving the stability and maintainability of the ShareDB backend. They initialized object properties for optimization, refactored tests to be more robust and less flaky, and implemented error handling with stack traces. Additionally, the user made modifications to the database interactions and test setup, demonstrating a good understanding of the backend architecture. The contributions improved code quality and testing.
backendoperational-transformationrealtime-database
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