Senior PM: GPU Kubernetes Runtime (Open Source)

Nvidia Corporation in; Santa Clara (CA); Hybrid; USD 208,000 - 380,000; Full time

Job summary

NVIDIA in California is seeking a Senior Product Manager for Kubernetes Accelerated Runtime (Finance) to lead the AICR project, set direction, and ensure the GPU software stack on Kubernetes is validated and reproducible.

You will expand coverage across accelerators, clouds, and workloads—from training to inference to agentic AI—and represent AICR to customers, partners, and the open-source community.

Qualifications

• 12+ years in technical product management across cloud infrastructure, Kubernetes, or developer and platform tooling.
• Bachelor's or master's degree in a relevant field, or equivalent experience.
• Depth in the Kubernetes GPU stack: cluster provisioning and lifecycle, operators and drivers, scheduling, and compatibility across kernel, driver, OS, and Kubernetes versions.
• Experience with GitOps and cluster configuration delivery (Helm, Argo CD, Flux, or equivalent tools).
• Track record of contributing to open-source projects, including community strategy and external presence such as conference talks or technical writing.

Responsibilities

• Own AICR and related technologies, set product direction, and standardize how customers and partners run NVIDIA's GPU software stack on Kubernetes.
• Expand coverage across accelerators, clouds, and workloads, from training and inference to agentic AI.
• Keep the stack current and trustworthy, turning NVIDIA's validation into recipes that customers can deploy with supply-chain confidence.
• Represent AICR and other NVIDIA projects to customers and partners, and lead their growth in the open-source community.

Skills

Kubernetes GPU

Cloud infrastructure

Open-source community

GitOps

Product strategy

Education

Bachelor's or Master's in a relevant field

Tools

Helm

Argo CD

Flux

Sigstore

Cosign

Job description

NVIDIA in California is seeking a Senior Product Manager for Kubernetes Accelerated Runtime (Finance) to lead the AICR project, set direction, and ensure the GPU software stack on Kubernetes is validated and reproducible.

You will expand coverage across accelerators, clouds, and workloads—from training to inference to agentic AI—and represent AICR to customers, partners, and the open-source community.