NVIDIA is seeking a Senior Staff SRE to build and operate reliable, scalable compute platforms that support global engineering workloads. This role spans Kubernetes, KubeVirt, bare-metal infrastructure, automation, observability, and AI-enabled operations.
Join a team that solves complex infrastructure challenges, builds durable automation, and improves the reliability and operational experience of critical compute services.
What you’ll be doing:
Build, operate, and improve large-scale Kubernetes, KubeVirt, Linux, container, and bare-metal compute platforms, with a focus on performance, capacity, reliability, and operational scale.
Lead bare-metal provisioning and lifecycle management in data centers, including PXE boot, DHCP, DNS, OS provisioning, hardware validation, and fleet automation.
Develop automation, self-service capabilities, and observability solutions using APIs, Python or Go, Infrastructure as Code, configuration management, metrics, logs, traces, and service-health data.
Define and operate SLOs, SLIs, error budgets, alerting, and incident-response practices; lead complex incident investigations, corrective actions, and blameless postmortems.
Partner with infrastructure, security, hardware, data-center, and application teams to deliver global platform initiatives, and participate in an on-call rotation.
What we need to see:
BS in Computer Science, Engineering, a related technical field, or equivalent experience, plus 10+ years operating production infrastructure or platform services.
Strong expertise in Kubernetes administration, KubeVirt, Docker, containerization, microservices, Linux systems, and resolving distributed-system challenges.
Experience deploying and operating bare-metal infrastructure in a data-center environment, including provisioning, networking, operating-system lifecycle management, and hardware automation.
Proficiency in Python, Go, or a comparable programming language, with experience building RESTful services and integrating infrastructure APIs.
Experience with Infrastructure as Code and automation tools such as Terraform, Ansible, Chef, or Puppet, along with a solid understanding of TCP/IP networking and infrastructure security.
Strong SRE and observability experience, including SLIs, SLOs, error budgets, incident management, monitoring, logging, tracing, and tools such as OpenTelemetry, Prometheus, Grafana, ELK Stack, or Splunk.
Clear written and interpersonal communication skills, with a record of delivering practical, scalable solutions to complex technical problems.
Ways to stand out from the crowd:
Experience operating HPC, AI, GPU-accelerated, or general-purpose bare-metal compute infrastructure, including GPU-enabled Kubernetes or KubeVirt clusters.
Expertise with VMware vSphere, Red Hat OpenShift, KVM, Firecracker, OpenStack, or Nutanix AHV.
Experience applying generative AI or agentic workflows to improve infrastructure diagnostics, reduce operational toil, and accelerate incident resolution.
Experience building secure, integrated operational platforms using APIs, RBAC, service accounts, secrets management, audit controls, workflow orchestration, and infrastructure or incident-management systems.
Demonstrated delivery of complex, high-impact infrastructure projects.
Skills Required
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent experience
- 10+ years of experience operating production infrastructure or platform services
- Strong expertise administering Kubernetes and experience with KubeVirt, Docker, containerization, microservices, and Linux systems
- Experience deploying and operating bare-metal infrastructure in data-center environments
- Experience with provisioning, networking, operating-system lifecycle management, and hardware automation
- Proficiency in Python, Go, or a comparable programming language
- Experience building RESTful services and integrating infrastructure APIs
- Experience with Infrastructure as Code and automation tools such as Terraform, Ansible, Chef, or Puppet
- Understanding of TCP/IP networking and infrastructure security
- Strong SRE and observability experience with SLIs, SLOs, error budgets, incident management, monitoring, logging, and tracing
- Clear written and interpersonal communication skills
- Experience operating HPC, AI, GPU-accelerated, or general-purpose bare-metal compute infrastructure
- Experience with GPU-enabled Kubernetes or KubeVirt clusters
- Expertise with VMware vSphere, Red Hat OpenShift, KVM, Firecracker, OpenStack, or Nutanix AHV
- Experience applying generative AI or agentic workflows to infrastructure operations
- Experience building secure operational platforms using APIs, RBAC, service accounts, secrets management, audit controls, and workflow orchestration
- Demonstrated delivery of complex, high-impact infrastructure projects
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
