Scott Leishman
Software Engineer at Leishman Labs LLC
San Diego, California, United States
Summary
🤩
Rockstar🎓
Top SchoolScott Leishman is a seasoned software engineer with 16 years of experience building and running production ML and cloud systems, now based in San Diego. He has led teams at Intel and Nervana where he architected deep learning orchestration and helped launch one of the first MLaaS offerings, and more recently has driven engineering and product efforts at startups and through his own consultancy. His open-source contributions span deep learning infrastructure and tooling—improving CI/CD, containerized builds, and CUDA-enabled libraries—helping projects like Intel’s neon and Reinforcement Learning Coach become more robust and deployable. Comfortable both as an individual contributor and as a technical manager, he combines hands-on backend and DevOps skills with experience scaling teams to 60+ engineers. He brings a pragmatic focus on reproducibility, testing, and deployment automation that shortens the path from research code to production. Trained at the University of Toronto, he blends academic rigor with startup pragmatism and a knack for untangling build and integration pain points.
16 years of coding experience
17 years of employment as a software developer
Master of Science Computer Science, Master of Science Computer Science at University of Toronto
Stackoverflow
460reputation
34kreached
5answers
0questions
Github Skills (28)
kubernetes10
docker10
gpgpu10
python10
build-system10
dockers10
reinforcement-learning10
cicd10
deep-learning10
gpu10
kubernetes-pods10
accelerated-computing10
cuda10
documentation10
setuptools9
Programming languages (10)
Github contributions (5)
NervanaSystems/neon
May 2015 - Apr 2016
Intel® Nervana™ reference deep learning framework committed to best performance on all hardware
Role in this project:
Back-end Developer
Back-end DeveloperContributions:17 releases, 165 commits, 34 PRs in 1 year
Contributions summary:Scott primarily contributed to documentation updates, including fixing broken links and updating documentation links within the project. They also made updates to test and example configurations, and addressed a minor issue within the deep learning framework itself. Their work focused on ensuring integration tests run correctly and fixing serialization issues.
deep-learningbest-performanceintelmachine-learningperformance
IntelLabs/coach
Nov 2018 - Aug 2019
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Role in this project:DevOps Engineer
DevOps EngineerContributions:17 commits, 27 PRs, 55 pushes in 9 months
Contributions summary:Scott primarily focused on improving the CI/CD pipeline and build processes. They implemented Dockerfiles for different environments, ensuring parallelization of test runs and resolving issues related to CI setup and EKS token refresh. The user also updated the build process to include StarCraft environment and functional testing capabilities. Furthermore, they broadened the supported package versions and updated the project's dependencies.
starcraftstate-of-the-artdeep-reinforcement-learningstarcraft2carla
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