William Irons
Advisory Software Enginner - Watson Machine Learning Community Edition
Rochester, Minnesota, United States
Summary
👤
Senior🎓
Top SchoolWilliam Irons is an experienced software engineer with 10+ years at IBM, currently advising on Watson Machine Learning Community Edition and porting the TensorFlow family to IBM Power systems. He blends hands-on build-and-release expertise with systems-level troubleshooting, having led teams delivering private cloud management interfaces and integrated rack solutions under tight deadlines. William is a pragmatic open source contributor and DevOps engineer who optimized TensorFlow builds for ppc64le—tuning Dockerfiles, CUDA/CUDNN/Bazel versions, and cache strategies to improve performance and packaging as conda artifacts. His background spans storage and virtualization APIs, large-scale verification triage, and automation with Python, Ansible, and shell scripting, giving him a rare cross-stack perspective from firmware to ML frameworks. Based in Rochester, Minnesota, he thrives on diving into code to understand and fix hard problems, often surfacing non-obvious dependency and build issues that block production deployments.
10 years of coding experience
19 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Michigan Technological University
Stackoverflow
2,334reputation
306kreached
41answers
0questions
tensorflow
top-5%
anaconda
top-5%
python
top-5%
conda
top-5%
Github Skills (25)
docker10
bash10
dockers10
cicd10
script10
tensorflow10
build-automation10
ubuntu9
python9
conda9
bazel9
anaconda9
cuda9
github-ci7
githubaction-workflow7
Programming languages (9)
Github contributions (5)
ppc64le/build-scripts
Aug 2018 - Mar 2020
Build scripts for open source projects on Linux on POWER LE
Role in this project:
DevOps Engineer & Build/Release Engineer
DevOps Engineer & Build/Release EngineerContributions:27 commits, 24 PRs, 4 pushes in 1 year 6 months
Contributions summary:William primarily contributed to the build and deployment infrastructure of the TensorFlow project on the ppc64le architecture. Their work involved creating and modifying Dockerfiles to build TensorFlow and TensorFlow Serving, including specifying CUDA, CUDNN, and Bazel versions. They also focused on improving build performance by optimizing caching strategies and updating the publish script. Furthermore, the user addressed issues related to dependencies like scipy and h5py, ensuring the build process functions correctly.
build-scriptslinuxpowerdistro
wdirons/build-scripts
Aug 2018 - May 2020
Build scripts for open source projects on Linux on POWER LE
Contributions:35 pushes, 43 branches in 1 year 9 months
build-scriptslinuxpower
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