Paul Taylor
Senior Software Engineer at NVIDIA
Portland, Oregon, United States
Summary
🤩
RockstarPaul Taylor is a Senior Software Engineer based in Portland, Oregon with 14 years of experience building high-performance systems across CUDA C++, JavaScript, and Python. At NVIDIA he focuses on RAPIDS and CUDA core libraries, contributing to GPU-accelerated projects like cuGraph, cuDF, cuML and the RAPIDS memory and algorithm stacks. He has deep open-source chops—co-authoring or contributing to projects such as Apache Arrow’s JavaScript implementation, ReactiveX/IxJS build tooling, and performance work in sccache—bridging low-level performance engineering with developer-facing tooling. Paul’s background includes front-end platform work at Netflix (RxJS/Falcor) and visualization-focused engineering at Graphistry, giving him a rare full-stack perspective on data pipelines and UI. He frequently improves build systems, CI/CD and release automation, and is known for pragmatic fixes that improve portability and memory efficiency in large C++/CUDA codebases. That blend of systems performance, developer tooling, and JavaScript ecosystem experience makes him effective at turning research-grade GPU algorithms into production-ready developer tools.
14 years of coding experience
10 years of employment as a software developer
Stackoverflow
171reputation
18kreached
9answers
0questions
Github Skills (70)
dependency-management10
graph-algorithms10
python10
testing10
cmake10
apache-arrow10
gpu10
build-automation10
cython10
random-forest10
integration-testing10
operator10
javascript10
gpgpu10
memory-management10
Programming languages (19)
Github contributions (5)
rapidsai/cuspatial
Mar 2020 - Jan 2023
CUDA-accelerated GIS and spatiotemporal algorithms
Role in this project:
Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:224 reviews, 395 commits, 79 PRs in 2 years 10 months
Contributions summary:Paul contributed to the development of CUDA-accelerated GIS and spatiotemporal algorithms. Their work included adding a CMake variable for GPU architectures, parallelizing Cythonization, and fixing linting issues. They also focused on infrastructure, reverting changes to setup.py to resolve conda-build issues and integrating a more memory-efficient approach for building the project.
cudagpu-programminggpu-accelerationgpuaccelerated
ReactiveX/IxJS
Aug 2017 - Aug 2022
The Interactive Extensions for JavaScript
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:36 releases, 17 reviews, 316 commits in 5 years
Contributions summary:Paul primarily contributed to build and deployment tasks, integrating new features and fixing existing ones. They added support for TypeScript targets and updated the build scripts to include new modules and ES2015 UMD bundles. The user was also responsible for automating publishing and release processes with scripts to handle version bumping and changelog generation. Additionally, they fixed linting issues and updated test files.
javascriptextensionsjsxchrome-extension
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