$272,000 – $431,250
Listed on NVIDIA’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads engineering on NVIDIA's Kubernetes fleet management platform for GPU-accelerated AI infrastructure, designing systems that automate cluster provisioning, upgrades, and lifecycle management at scale. It suits experienced systems engineers with deep Kubernetes expertise who want to architect cloud-native infrastructure that powers AI teams globally.
Our summary, not NVIDIA’s wording. The full posting is on their site.
Skills this role names
Log in to see which of these are already on your profile.
What they ask for
Required
- BS/MS in Computer Science or related field or equivalent experience
- 15+ years of work experience in large scale environments
- Expert-level systems programming in Go and C with strong Data Structures and Algorithms knowledge
- Strong knowledge of Kubernetes and container technology
- In-depth understanding of Unix/Linux kernel internals
- Hands-on automation experience with modern infrastructure tools
- Experience setting up, maintaining, and automating continuous deployment systems
- Strong background in cloud computing and distributed software design
Nice to have
- Extensive Go programming experience
- Deep understanding of rack-scale GPU systems
- Strong background with GitLab, Argo, Flux, and other CI/CD systems
- Significant hands-on experience with containers and Kubernetes
- Hands-on experience with container workload isolation and confidential computing