AJ Schmidt
Sr. DevOps Engineer at NVIDIA
Philadelphia, Pennsylvania, United States
Summary
🤩
Rockstar🎓
Top SchoolAJ Schmidt is a seasoned infrastructure and DevOps engineer with a decade of experience building and managing GPU-enabled CI/CD platforms, currently at NVIDIA where he led migration of 15+ large open-source repositories from Jenkins to GitHub Actions and ran self-hosted GPU runners. He combines hands-on automation (TypeScript, Go, Python), CI/CD optimization (sccache, conda, Docker), and CUDA-adjacent contributions across RAPIDS projects like cuDF, cuML, and RAFT to improve testing, builds, and documentation for high-performance ML libraries. As an Infrastructure Engineering Manager he balanced team leadership with operational ownership of on-prem and AWS infrastructure powering automated builds and deployments. Beyond code and pipelines, he brings attention to developer experience—authoring tools and test adapters that translate notebook logs to JUnit XML and streamline benchmarking metadata. Based in Philadelphia, he pairs technical breadth with practical delivery and unwinds off-hours at the piano, on the soccer field, or over a game of billiards.
10 years of coding experience
14 years of employment as a software developer
Bachelor of Science (BS) Electrical and Electronics Engineering, Bachelor of Science (BS) Electrical and Electronics Engineering at Drexel University
Stackoverflow
93reputation
4kreached
1answer
3questions
Github Skills (51)
github-ci10
sparse-array10
c-language10
github10
python10
testing10
sparse-matrix10
conda10
build-system10
bash10
cmake10
sparse-file10
java10
cicd10
javas10
Programming languages (27)
Github contributions (5)
rapidsai/cuspatial
Mar 2020 - Jan 2023
CUDA-accelerated GIS and spatiotemporal algorithms
Role in this project:
Back-end Developer
Back-end DeveloperContributions:169 reviews, 60 commits, 89 PRs in 2 years 9 months
Contributions summary:AJ primarily contributed to the `cuspatial` repository, focusing on CUDA-accelerated GIS and spatiotemporal algorithms. Their commits involved modifying CUDA code, specifically within the `cpp/src` directory. These modifications included changes to cubic spline interpolation, quadtree construction, and Hausdorff distance calculations. Furthermore, the user updated build scripts and documentation, demonstrating a focus on the core functionality and maintainability of the library.
cudagpu-programminggpu-accelerationgpuaccelerated
rapidsai/rmm
May 2020 - Jan 2023
RAPIDS Memory Manager
Role in this project:DevOps Engineer
DevOps EngineerContributions:180 reviews, 86 commits, 126 PRs in 2 years 9 months
Contributions summary:AJ primarily focused on maintaining and updating the repository's build and documentation processes. Their contributions included updating the documentation build script, making changes to the CI/CD configuration, and updating conda recipes. They were also involved in replacing `ccache` with `sccache` and adjusting upload scripts for the conda packages. The user's work centered on improving the build infrastructure and ensuring consistent deployments.
cudamemory-managementmemorycpppython
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