Senior Software Engineer - Accelerated Kubernetes Runtime Team

NVIDIA•US, WA, Remote, WA

1d•$184,000 - $356,500

About The Position

Join NVIDIA's Accelerated Kubernetes Runtime team to build GPU-accelerated Kubernetes runtime distributions. The role designs and builds automation systems that let engineers install, upgrade, and manage cluster runtime packages powering NVIDIA AI Accelerators. It includes developing controller systems that optimize runtime components for current and upcoming GPU architectures, including GB200/GB300 and Vera Rubin, while providing reliable, secure, and performant infrastructure. The Runtime team provides an NVIDIA-Accelerated Kubernetes runtime applicable to clusters using NVIDIA accelerators. Its automation-first, self-service tools aim to minimize manual effort and improve reliability and reproducibility. The position focuses on orchestrating runtime component lifecycles across thousands of Kubernetes clusters, and on systems for configuring, packaging, validating, and distributing accelerated compute components.

Requirements

Bachelor's degree in Computer Science or equivalent experience.
At least 8 years of professional experience, including at least 3 years of Kubernetes development experience.
Experience building production Kubernetes systems, with significant expertise in controllers, operators, and CustomResourceDefinitions.
Strong proficiency in Go and experience building scalable Go services that manage complex distributed systems.
Hands-on experience with Helm, Kustomize, and Kubernetes manifest packaging and templating.
Demonstrated ability to design and implement automation systems that replace manual processes with reliable, self-service tooling.

Nice To Haves

Experience with NVIDIA Kubernetes components, such as GPU Operator, device plugins, or other HPC components, in large-scale production environments.
Deep familiarity with OCI registries, artifact signing, SBOM generation, and supply chain security practices.
Experience building multi-tenant platform services, with a focus on API design, versioning, and backward compatibility.
Track record of migrating legacy systems to modern, automated platforms while maintaining zero-downtime operations.
Contributions to upstream Kubernetes/CNCF projects or experience extending Kubernetes API machinery.
Deep understanding of Kubernetes architecture, including API machinery, admission controllers, and resource lifecycle management.

Responsibilities

Design and implement runtime features that orchestrate the lifecycle of runtime components across thousands of Kubernetes clusters without manual intervention.
Build and maintain systems that configure, package, validate, and distribute accelerated compute components.
Develop Kubernetes controllers, CRDs, and operators that automate runtime installation, upgrade, and rollback operations through API-driven workflows.