Senior Kubernetes Runtime Engineer - GPU-Accelerated Platform

NVIDIA Corporation; United States; On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA Corporation is seeking a Senior Software Engineer for its Accelerated Kubernetes Runtime team to design, build, and automate GPU-accelerated Kubernetes runtime distributions. You will craft controller systems, define operators and CRDs, and optimize runtime components for NVIDIA GPUs across scalable clusters.

You will join a tight-knit team delivering automation-first, self-service tooling to streamline installation, upgrades, and management of cluster runtimes.

Qualifications

• Bachelor's degree in Computer Science or equivalent experience
• 8+ years of professional experience with at least 3 years Kubernetes development
• Experience building production Kubernetes systems with controllers, operators, and CRDs
• Strong proficiency in Go and building scalable Go services
• Hands-on with Helm, Kustomize, and managing Kubernetes manifests
• Demonstrated ability to design and implement automation systems that replace manual processes with reliable, self-service tooling

Responsibilities

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

Skills

Kubernetes

Go

CRDs

Controllers

Operators

Helm

Kustomize

Automation

Distributed systems

Education

Bachelor's in Computer Science

Tools

Kubernetes

Helm

Kustomize

Job description

NVIDIA Corporation is seeking a Senior Software Engineer for its Accelerated Kubernetes Runtime team to design, build, and automate GPU-accelerated Kubernetes runtime distributions. You will craft controller systems, define operators and CRDs, and optimize runtime components for NVIDIA GPUs across scalable clusters.

You will join a tight-knit team delivering automation-first, self-service tooling to streamline installation, upgrades, and management of cluster runtimes.