As a Software Engineer on NVIDIA's Accelerated Kubernetes Runtime team, you will design and build automation systems that enable seamless installation, upgrade, and management of cluster runtime packages for NVIDIA’s AI accelerators. You’ll work on innovative controller systems optimizing runtime components for the latest GPU architectures like GB200/GB300 and Vera Rubin. Your daily tasks include designing runtime features to orchestrate component lifecycles across thousands of Kubernetes clusters, building and maintaining systems that configure, package, validate, and distribute accelerated compute components, and developing Kubernetes controllers, CRDs, and operators for automated installation, upgrade, and rollback operations. The role requires a Bachelor’s in Computer Science or equivalent experience, 8+ years of professional experience with at least 3 years in Kubernetes development, strong proficiency in Go, and hands-on experience with Helm, Kustomize, and Kubernetes manifest packaging. Additionally, familiarity with NVIDIA Kubernetes components, OCI registries, artifact signing, SBOM generation, multi-tenant platform services, and contributions to upstream Kubernetes/CNCF projects is highly valued.
Design and implement automation systems for seamless installation and management of runtime components across Kubernetes clusters.
Build and maintain systems that configure, package, validate, and distribute accelerated compute components for NVIDIA GPUs.
Develop Kubernetes controllers, CRDs, and operators to automate the lifecycle operations of runtime components with API-driven workflows.
Ensure reliable, secure, and performant infrastructure for AI researchers and developers by optimizing runtime components for latest GPU architectures.
Work on migrating legacy systems to modern automated platforms while maintaining zero-downtime operations in large-scale production environments.
What we're looking for
8+ years of professional experience with at least 3 years in Kubernetes development.
Strong proficiency in Go for building scalable services managing distributed systems.
Experience designing and implementing automation systems replacing manual processes.
Hands-on expertise with Helm, Kustomize, and Kubernetes manifest packaging.
Deep familiarity with OCI registries and supply chain security practices.
Track record of migrating legacy systems to automated platforms with zero-downtime.
Market check
Salary context
Above market
How this pay compares to similar roles
Similar $168k
This role $236k
$97k
most similar roles pay here
$308k
This role pays more than
91%
of similar roles. Most pay
$139,100–$196,750
— the shaded band above.
At the midpoint, this role pays about
$236k
versus about
$168k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
824 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 812 roles with salary data.
Go
Kubernetes
Containerd
Linux
Cloud Computing
Distributed Systems
Data Structures
Algorithms
CI/CD
CNCF
Prometheus
Grafana
Terraform
AWS
Git
Docker
C++
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PostgreSQL