NVIDIA
Technology
DevOpsEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“DevOps Engineer at NVIDIA. Skills: Kubernetes, CI/CD, Cloud infrastructure, On-prem systems. Design Kubernetes infrastructure. Build Kubernetes infrastructure”
Industry & Context.
Troubleshooting
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, 3+ years in DevOps role, 3+ years in SRE role, 3+ years in infrastructure engineering role, Hands-on proficiency with Kubernetes, Hands-on proficiency with container tooling, Production environments experience, Track record building CI/CD pipelines, Track record maintaining CI/CD pipelines, Runner management experience, Pipeline-as-code experience, Fluency using AI-assisted development tools, Solid Linux administration skills, Fluency in Bash, Practical background with major cloud platform, Working knowledge of GitOps workflows, Collaboration mentality, Ownership mentality, Accountability to operate business-critical systems
Nice to Have
Azure preferred, AWS preferred, GCP preferred, On-prem Kubernetes at scale experience, Cluster bootstrap experience, MetalLB configuration experience, Ingress configuration experience, Secret management via HashiCorp Vault experience, Secret management via Azure Key Vault experience, Secret management via Sealed Secrets experience, SQL operational background, MongoDB operational background, Backups experience, Replication experience, Performance tuning experience, Observability improvements with Datadog experience
What You'll Do.
Design Kubernetes infrastructure
Build Kubernetes infrastructure
Operate Kubernetes infrastructure
Manage autoscaling with Keda
Manage GPU-enabled workloads
Extend CI/CD pipelines
Harden CI/CD pipelines
Manage GitLab runners
Evolve GitOps-based deployments
Maintain on-prem infrastructure
Improve on-prem infrastructure
Manage container platforms
Improve observability
Shorten time-to-recovery
Contribute to cluster rollouts
Contribute to AKS upgrades
Contribute to node pool reorganization
Contribute to GPU cluster enablement
Contribute to secret management
Automate provisioning
Automate configuration
Troubleshoot full stack issues
Turn incidents into improvements
How You'll Work.
Team & Collaboration
Partner with development teams; Partner with data teams; Partner with architecture teams
Process & Methodology
GitOps workflows
Full Job Description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA's Manufacturing Information Systems team builds the data and automation backbone that keeps global manufacturing operations running — from CI/CD and container platforms to the on-prem environments that production workflows depend on. Our DevOps team leads that infrastructure end-to-end: Azure cloud, Kubernetes at scale, delivery coordinated via GitLab, and multiple business-critical on-prem sites . With major initiatives on the roadmap — GPU-enabled Kubernetes, per-site cluster rollouts, AKS upgrades, and a broader Vault rollout — the work ahead offers a rare mix of greenfield infrastructure and hands-on stewardship of systems NVIDIA relies on daily. The team is small, senior, and deeply accountable, with a strong mentorship culture under an experienced tech lead. We are adding a third DevOps engineer to increase delivery capacity, reduce single-person risk on critical systems, and grow our database infrastructure capability from within. If building resilient cloud and on-prem systems at scale sounds like the right challenge, we'd like to hear from you. **What you 'll be doing:** * Design, build, and operate Kubernetes infrastructure across Azure AKS and on-prem clusters, including ingress, autoscaling with Keda, TLS management, and GPU-enabled workloads * Extend and harden CI
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