Richard Taylor
General Manager at TSR Group
Beaverton, Oregon, United States
Summary
🤩
Rockstar🎓
Top SchoolRichard Taylor is a results-oriented General Manager with a multi-decade track record driving factory and operations performance, from startup ventures to large semiconductor fabs. He has led accelerated technology ramps and capacity expansions—scaling outputs by 300% and managing sites with hundreds of employees and budgets in the hundreds of millions—while delivering multimillion-dollar cost reductions through supplier and equipment partnerships. Skilled in Lean, Six Sigma, program management and strategic process transformation, he repeatedly aligns organizations to financial goals and world-class operational metrics. Currently growing a durable medical equipment business in Beaverton, he pairs hands-on operations leadership with financial and marketing oversight. Less obvious: he has practical exposure to modern engineering toolchains through hands-on contributions to high-profile open-source projects like PyTorch’s ROCm testing infrastructure, reflecting an ability to bridge legacy manufacturing expertise with contemporary software-driven hardware validation.
4 years of coding experience
18 years of employment as a software developer
The University of ArizonaMBA, MBA at St.Edward's University
Github Skills (13)
hip10
pytorch10
roc10
python10
cicd10
testing10
gpu9
triton9
c-language8
cprogramming-language8
devops8
machine-learning7
deep-learning7
Programming languages (7)
Github contributions (5)
pytorch/pytorch
Sep 2022 - Jan 2023
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:101 reviews, 3 commits, 243 PRs in 4 months
Contributions summary:Richard primarily contributed to the PyTorch testing infrastructure, specifically focusing on ROCm (AMD) support. Their commits involved modifying test scripts and code to ensure compatibility with ROCm platforms, including adjusting device visibility and managing environment variables. They also worked on fixing issues related to the Inductor backend for ROCm and incorporated the latest AMD backend integration. Furthermore, the user addressed performance and accuracy issues in layer normalization and flex attention kernels.
gpu-accelerationneural-networkpythonautogradgpu
jataylo/pytorch
Jul 2022 - Jul 2026
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:1 PR, 513 pushes, 196 branches in 4 years
gpu-accelerationneural-networkpython
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