Renaud Gaubert
Member Of Technical Staff at OpenAI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRenaud Gaubert is a pragmatic software engineer with a decade of experience building GPU-aware cloud-native infrastructure and tooling, currently helping build OpenAI’s supercomputers after leading NVIDIA’s OSS container and cloud-native efforts. He combines deep kernel- and systems-level knowledge with DevOps and CI expertise, having contributed substantial features to projects like Docker, Moby, Kubernetes and key NVIDIA runtimes and operators. At NVIDIA he led efforts to integrate GPUs across containers and orchestrators, improved CI/build systems, and drove adoption of GPU workflows across large engineering teams and datacenter bring-ups. An active open-source contributor, his work on generic resources, device plugins and GPU monitoring touches widely used repos (docker/cli, kubernetes, moby and libnvidia-container). He’s comfortable across the stack—from runc and runtime integration to Helm, e2e tests and Prometheus exporters—and uniquely blends hands-on coding with architecture, mentoring and operational hardware debugging. Based in San Francisco, he pairs formal computer science training with business-minded MBA studies, enabling both technical depth and cross-organizational leadership.
11 years of coding experience
7 years of employment as a software developer
Computer Science, Computer Science at University of California, BerkeleyMaster's degree, Computer Science, Master's degree, Computer Science at EPITA: Ingénierie InformatiqueMBA in Business Intelligence, Risk Management, Lobbying and Crisis management, MBA in Business Intelligence, Risk Management, Lobbying and Crisis management at Ecole de Guerre Economique
French, English
Github Skills (39)
kubernetes10
container10
docker10
gnu-make10
monitor10
api-design10
scripting10
testing10
bash10
c1110
makefile10
containerization10
dockers10
cicd10
c1710
Programming languages (13)
Github contributions (5)
NVIDIA/gpu-monitoring-tools
Aug 2019 - Jul 2020
Tools for monitoring NVIDIA GPUs on Linux
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:86 commits, 9 PRs, 73 pushes in 11 months
Contributions summary:Renaud primarily contributed to the back-end functionality of the GPU monitoring tools. Their work involved adding device compute capability information by modifying Go bindings, including the `nvml.go` and `bindings.go` files. The user also made improvements to the project by fixing naming issues and addressing errors. Furthermore, the user implemented changes to the code related to the CPU affinity and the NVLINK enumeration.
linuxmonitoringnvidia
NVIDIA/gpu-operator
Feb 2019 - Oct 2020
NVIDIA GPU Operator creates, configures, and manages GPUs in Kubernetes
Role in this project:DevOps Engineer
DevOps EngineerContributions:209 commits, 3 PRs, 422 pushes in 1 year 7 months
Contributions summary:Renaud Gaubert's contributions primarily revolve around improving the Continuous Integration (CI) pipeline and managing the build process for the NVIDIA GPU Operator. They refactored Dockerfiles, updated the Golang version, and streamlined the CI process. Furthermore, they addressed a Helm-related deployment bug and added e2e tests.
gpukubernetesnvidiaoperatorcuda
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