NVIDIA
Senior Site Reliability Engineer - Kubernetes Platform
$184K–$356K
US, CA, Santa Clara +2 · Senior · Full-time · Posted Oct 11, 2026
- Location
- US, CA, Santa Clara
US, TX, Austin
US, NC, Durham - Experience
- 8+ years building and supporting critical production services; 5+ years of coding/scripting in at least two languages.
- Education
- Bachelor's degree in Computer Science or related technical field (or equivalent experience).
About the job
Own and scale NVIDIA’s Kubernetes platform for chip-design workloads across on-premises datacenters and public clouds, improving reliability, automation, and operations.
What you'll do
- Manage Kubernetes clusters end-to-end and implement multi-cluster lifecycle, upgrade, and rollout strategies.
- Build infrastructure-as-code, GitOps, observability, and automated recovery practices; lead on-call incident response and root-cause analysis.
- Partner with EDA, storage, network, and data center teams to design and improve platform capabilities and deployments.
What they ask for
- Bachelor's degree in Computer Science or related technical field (or equivalent experience).
- Hands-on production Kubernetes operations experience, including CSP-managed and self-managed on-premises Kubernetes across multiple datacenters.
- Strong CI/CD and Infrastructure-as-Code experience; proficiency with monitoring, metrics, and log collection tooling.
- 5+ years of coding/scripting for automation and operational management at scale in at least two languages; track record mentoring engineers and influencing technical direction.
Nice to have
- Familiarity with EDA/silicon-design workflows, license management, or license-constrained compute; production Kubernetes controllers, operators, or plugins.
- Experience with large-scale stateful, storage-heavy, or GPU-accelerated Kubernetes workloads; technical publications or open-source maintenance.
Pay
184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)
Tools
Kubernetes, EKS, GKE, RKE, Red Hat OpenShift, Terraform, Ansible, Helm
AI focus
Build data-driven and auto-healing operations, including AIOps/ML-driven signals, and support intelligent workload routing, dynamic scaling, and resource governance.
Model-written summary · the original posting is authoritative