Michael Hudgins
Staff Software Engineer at Google
Indianapolis, Indiana, United States
Summary
🤩
Rockstar🎓
Top SchoolMichael Hudgins is a Staff Software Engineer in Indianapolis with 8 years of experience building cloud architecture, ML infrastructure, and scalable developer tooling. Currently at Google leading ML DevInfra and OSS ML Velocity work, he combines hands-on DevOps engineering with system design to optimize large build and CI/CD pipelines. His open-source contributions to flagship projects like JAX, XLA, and TensorFlow focus on build infrastructure, remote execution, and cross-platform build reliability—work that materially reduces test times and eases ARM64/CUDA build pain points. Previously he led cloud product architecture and desktop application engineering at Imagine Products, and he runs his own software shop, Keisarian Applications. A strong academic performer (BS CS, 3.96 GPA), he brings both engineering depth and an operator’s mindset to shipping resilient, production-grade ML systems.
8 years of coding experience
13 years of employment as a software developer
Bachelor of Science (BS), Computer Science, 3.96, Bachelor of Science (BS), Computer Science, 3.96 at Indiana University-Purdue University at Indianapolis
Github Skills (19)
docker10
bash10
dockers10
cicd10
tensorflow10
bazel10
build-automation10
arm10
jax10
github-ci9
python9
linux9
githubaction-workflow9
macos9
cuda9
Programming languages (15)
Github contributions (5)
jax-ml/jax
Sep 2023 - Mar 2025
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Role in this project:
DevOps Engineer
DevOps EngineerContributions:9 reviews, 176 PRs, 6 pushes in 1 year 6 months
Contributions summary:Michael's contributions primarily involve modifying build configurations and CI/CD related scripts. They updated the XLA dependency to use `tf_http_archive` for Bazel mirrors, and adjusted references in setup and utility scripts to reflect organizational changes. Furthermore, the user's commits include merging branch changes, suggesting involvement in broader project integration. These changes directly impact build processes and infrastructure configuration within the repository.
pytorchpythonjitautomatic-differentiationgpu
openxla/xla
Aug 2022 - Jan 2023
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:DevOps Engineer
DevOps EngineerContributions:1 review, 14 commits, 7 PRs in 5 months
Contributions summary:Michael primarily contributed to improving the build and test infrastructure. Their work included adding RBE (Remote Build Execution) to Linux builds to reduce test times, re-enabling the macOS presubmit, and addressing out-of-space issues in the macOS CI environment. Furthermore, the user modified the build process by updating specific bazel configurations and CI build scripts. These changes aimed to optimize the build and test process across different platforms.
compilercommunity-drivenmachine-learningmodular
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