Steven Robertson
Cloud Operations Engineer
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSteven Robertson is a Cloud Operations Engineer with 11 years of experience building and automating cloud infrastructure at companies including Palantir, Intel AI, and OctoML. He combines deep operational expertise with backend Python development, notably as a maintainer and contributor to Mitogen for Ansible—a project for distributed self-replicating Python programs that improves remote execution and interpreter compatibility. At Intel he streamlined benchmarking and deployment workflows, adding robustness and cross-version Python support for AI workloads on Xeon and Intel GPUs. Based in Oakland, he blends hands-on DevOps skills (ssh/sudo, container lifecycle handling, CI automation) with a pragmatic focus on reproducible, debuggable systems. Colleagues rely on him to solve tricky interpreter and environment issues that often break automation at scale. He’s active on GitHub and brings a quietly obsessive attention to edge cases that make production automation reliable.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at University of California, Davis
Spanish
Github Skills (21)
docker10
python10
bash10
dockers10
automation10
ansible10
ansible-galaxy10
automations10
devops10
cicd9
sudo9
ssh9
performance-analysis8
tensorflow8
performance-monitor8
Programming languages (6)
Github contributions (5)
mitogen-hq/mitogen
Oct 2019 - Mar 2021
Distributed self-replicating programs in Python
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:2 releases, 27 reviews, 301 commits in 1 year 5 months
Contributions summary:Steven primarily contributed to the `mitogen` project by enhancing its support for different Python interpreters, including special ones. They fixed issues related to the execution environment of the code. Moreover, the user made changes to support complex scenarios such as when the Ansible python interpreter requires specific path definitions. They modified aspects of the project relating to ssh and sudo commands.
raypythondevopsgeventinfrastructure
intel/ai-reference-models
Nov 2018 - Apr 2019
Intel® AI Reference Models: contains Intel optimizations for running deep learning workloads on Intel® Xeon® Scalable processors and Intel® Data Center GPUs
Role in this project:DevOps Engineer & Automation Engineer
DevOps Engineer & Automation EngineerContributions:12 commits, 8 PRs, 5 pushes in 4 months
Contributions summary:Steven's commits primarily focus on automating and improving the build and deployment processes within the repository. They made changes to the `start.sh` script to add functionalities and dependencies and updated the `launch_benchmark.py` script to enable enhanced debugging capabilities, including the ability to kill docker processes on Ctrl+C. The user also addressed Python 2/3 compatibility issues and implemented dynamic setting for the log directory. These contributions streamline the development and benchmarking workflows.
optimizationsprocessorstensorflowzoomodel-zoo
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