Josh Wilson
Staff Machine Learning Engineer at Reddit, Inc.
Alaska, United States
Summary
🤩
Rockstar🎓
Top SchoolJosh Wilson is a Staff Machine Learning Engineer with a decade of experience building scalable ML systems and production-grade scientific software, currently based in Alaska and leading ML efforts at Reddit. He blends deep academic training—a PhD in Computational and Applied Mathematics—with hands-on engineering across backend, DevOps, and QA roles, having shipped work at companies from Tempo Automation to Pylon. Josh is a frequent open-source contributor to cornerstone scientific projects like NumPy, SciPy, and Numba, improving type safety, documentation, and compiler support that benefit the broader Python scientific stack. He has strong low-level and HPC experience from work at Argonne National Laboratory, including MPI/OpenACC and running on TOP500 systems, which informs his ability to optimize performance-critical pipelines. Colleagues rely on him to translate complex numerical methods into maintainable, testable code and to improve build and packaging workflows for reproducible deployments. He’s known for quietly improving developer experience at scale—adding type stubs, refactoring code, and fixing subtle edge cases that reduce long-term maintenance burden.
10 years of coding experience
7 years of employment as a software developer
University of Minnesota Twin Cities
Github Skills (22)
debug10
pytest10
package-management10
python10
testing10
numpy10
typehinting10
starlark10
compiler-compiler10
bazel10
build-automation10
compiler10
pip10
type-checking10
numba10
Programming languages (12)
Github contributions (5)
scipy/scipy
Oct 2015 - May 2020
SciPy library main repository
Role in this project:
Back-end Developer
Back-end DeveloperContributions:51 reviews, 430 commits, 317 PRs in 4 years 8 months
Contributions summary:Josh primarily contributed to bug fixes and documentation improvements within the SciPy library. Their work involved fixing typos in the documentation, correcting an undocumented option in the `scipy.optimize.root` function, and resolving an issue related to handling complex values in a function. The user also refactored error handling and type stubs for various functions within the codebase, indicating a focus on code quality and usability. Additionally, they addressed several issues by updating testing tools and dependencies, improving code quality, and correcting implementation errors.
scipypythonscientific-computing
bazel-contrib/rules_python
Jan 2021 - Jan 2022
Bazel Python Rules
Role in this project:Backend & DevOps Engineer
Backend & DevOps EngineerContributions:12 reviews, 7 commits, 9 PRs in 1 year
Contributions summary:Josh primarily contributed to the Bazel Python rules project by enhancing the build system and package management. They added features for handling wheel dependencies and requirements files, ensuring correct dependencies during the pip install process. The user also addressed build and package structure issues, optimizing the build process and fixing various code problems. Furthermore, they introduced improvements for incremental builds and general project usability.
pythonpypibazelpipstarlark
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