Jesse Hellemn
Backend Software Engineer at Stem, Inc.
Tokyo, Japan
Summary
🤩
Rockstar🎓
Top SchoolJesse Hellemn is a backend software engineer with 11 years of experience building reliable server-side systems and streamlining build/release pipelines. He has production experience at Facebook and currently at Stem, and notable open-source contributions to heavyweight ML infrastructure like Caffe2 and PyTorch builder where he fixed operator bugs and hardened conda-based build and deployment scripts. Comfortable across Python, build systems, and DevOps, he focuses on automation, reproducible builds, and burst-fixing subtle out-of-bounds and packaging issues that can break large-scale ML workflows. Early work spans telemetry, data visualization, and custom NLP classifiers, reflecting a pragmatic blend of research curiosity and production rigor.
11 years of coding experience
3 years of employment as a software developer
Computer Science, Summer of Freshman Year, Computer Science, Summer of Freshman Year at The University of Texas at AustinBachelor of Science (BS), Computer Science and Statistics, Junior, Bachelor of Science (BS), Computer Science and Statistics, Junior at Rice UniversityPlano Senior High School
English
Github Skills (20)
docker10
c-language10
caffe10
python10
bash10
conda10
dockers10
cicd10
build-automation10
cprogramming-language10
devops10
pytorch9
machine-learning9
cmake9
aws9
Programming languages (9)
Github contributions (5)
pytorch/builder
Aug 2018 - Jul 2019
Continuous builder and binary build scripts for pytorch
Role in this project:
DevOps Engineer & Build/Release Engineer
DevOps Engineer & Build/Release EngineerContributions:405 commits, 376 PRs, 208 pushes in 11 months
Contributions summary:Jesse focused on improving the build and release process for the PyTorch project. They implemented support for specifying Python versions and git branches, and modified the build scripts to handle package naming and test execution, including adding smoke tests. The user was also involved in the deployment pipeline, creating scripts for uploading and updating links to S3, and adding improvements related to the conda builds. These changes suggest a focus on automating and streamlining the build, test, and release workflows.
pytorchbuild-scriptscontinuousbuilder
facebookarchive/caffe2
Dec 2017 - Apr 2018
Caffe2 is a lightweight, modular, and scalable deep learning framework.
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:89 commits, 101 PRs, 31 pushes in 4 months
Contributions summary:Jesse contributed to the Caffe2 framework by addressing bugs related to `PackSegments` operator, including adding length verification checks and resolving out-of-bounds issues. They also worked on improving the build process, evidenced by adding conda environments for Ubuntu and macOS builds. Furthermore, the user adapted the conda build scripts, adding a full build option, adjusting include directories, and fixing build errors, indicating work in build system and deployment.
pytorchscalablecaffe2deep-learningml
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