Ryan Soklaski
Member Of Technical Staff at Anthropic
Cambridge, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolRyan Soklaski is a machine learning researcher and senior Python developer with a PhD in computational physics and nine years of experience building robust, research-driven software for both academic and applied AI contexts. Currently a Member of Technical Staff at Anthropic, he previously led projects at MIT Lincoln Laboratory where he created hydra-zen and led open-source tooling and responsible-AI efforts that improved reproducibility and robustness in ML workflows. He is an award-winning educator who designed and taught the CogWorks course at MIT Beaver Works, and maintains popular open-source projects such as MyGrad and hydra-zen used by the Python scientific community. His contributions to flagship projects like NumPy and Hypothesis demonstrate deep expertise in testing and numerical correctness, while his research background in molecular dynamics and 2D materials underpins a rare blend of theoretical rigor and practical software engineering. Based in Cambridge, MA, Ryan combines high-impact publishing with scalable engineering and a track record of creating free educational resources that lower the barrier to learning ML.
10 years of coding experience
11 years of employment as a software developer
Bachelor’s Degree, Mathematics, 4.0, Bachelor’s Degree, Mathematics, 4.0 at Saint Louis UniversityDoctor of Philosophy (Ph.D.), Physics, 3.9, Doctor of Philosophy (Ph.D.), Physics, 3.9 at Washington University in St. Louis
Stackoverflow
540reputation
78kreached
9answers
0questions
Github Skills (19)
property-based-testing10
wordpress-themes10
python10
jupyter10
testing10
numpy10
ui-theme10
hy10
jupyter-notebook10
test-automation10
template-method-pattern6
graph6
networkx6
docstrings6
inheritance6
Programming languages (13)
Github contributions (5)
HypothesisWorks/hypothesis
Mar 2019 - Jan 2023
The property-based testing library for Python
Role in this project:
Backend Developer & Test Automation Engineer
Backend Developer & Test Automation EngineerContributions:73 reviews, 185 commits, 42 PRs in 3 years 10 months
Contributions summary:Ryan primarily contributed to the property-based testing library for Python by adding a new strategy, `valid_tuple_axes`, which generates tuples of axis indices. Their work involved writing the core logic of the strategy and creating several tests to ensure the validity and proper behavior of the new feature. Furthermore, the user addressed minor issues by fixing typos in release notes, resolving flake8 and black formatting, and adding intersphinx cross-references.
property-based-testingpythontestingfuzzing
numpy/numpy
May 2018 - Jan 2021
The fundamental package for scientific computing with Python.
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:9 commits, 7 PRs, 17 comments in 2 years 8 months
Contributions summary:Ryan primarily focused on improving the testing suite for the NumPy library. They addressed bugs related to the `einsum` function, specifically concerning broadcasting and singleton dimensions. Their work involved modifying existing tests, adding new test cases, and ensuring the robustness and correctness of the numerical computations within NumPy. The contributions highlight a focus on verifying the functionality of core mathematical operations.
pythonscientific-computingnumpy
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.