- Bachelor's degree in Computer Science or related technical field (or equivalent experience) with 8+ years building and supporting critical production services.
- Deep, hands-on Kubernetes operations experience - you've run it, not just consumed it. Comfortable debugging etcd, kubelet, CNI, CSI, scheduler behavior, API server load, container runtime, and control-plane degradation under real production pressure.
- Production experience with CSP-managed Kubernetes — including its upgrade model, networking and IAM integration, node group lifecycle, and where the managed abstraction stops helping you.
- Production experience operating self-managed Kubernetes on-premises across multiple datacenters — cluster bring-up, bare-metal and GPU node lifecycle, multi-site topology, and the failure modes that only show up when you own the whole stack.
- Strong command of CI/CD and Infrastructure-as-Code (Terraform, Ansible, Helm, Kustomize, Argo CD/Flux or equivalents).
- Demonstrated experience building large-scale infrastructure platforms for automated host lifecycle management, fleet reliability and auto-healing, end-to-end observability, or data-driven operations (AIOps/ML-driven signals) that measurably reduced toil.
- Proficiency with monitoring, metrics,, and log collection tooling (Prometheus, Grafana, OpenTelemetry, Loki/ELK, containerd, etc.).
- 5+ years of coding/scripting focusing on automation and operational management at scale in at least two languages such as Go, Python, Perl, or Ruby - with Go a strong plus for controller and operator work.
- Track record mentoring engineers and influencing technical direction through design reviews, architecture documents, and strong partnership with team members and leadership.
- Creative problem solver with excellent debugging instincts and strong written communication.
Ways to stand out from the crowd
- Familiarity with EDA/silicon-design workflows, license management, or other license-constrained compute environments. You've written or built Kubernetes controllers, operators, admission webhooks, scheduler plugins, or device/CSI plugins that ran in production.
- Experience running stateful, storage-heavy, or GPU-accelerated workloads on Kubernetes at scale.
- Published technical write-ups or talks (conference presentations, meetups, engineering blogs) that deep-dive into real-world reliability, observability, or large-scale Kubernetes/HPC problems.
- Maintainer or co-maintainer responsibilities for an open source component used in production at scale - operators, exporters, controllers, plugins, or SDKs.
We have some of the most forward-thinking and hard-working people in the world working for us and, due to unprecedented growth, our engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 9, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.