Build and operate automation, tooling, and services for large-scale GPU clusters across cloud and on-premises environments. Develop provisioning, validation, upgrades, monitoring, repair, GitOps, and lifecycle workflows. Improve Day 0–Day 2 operations, reduce manual intervention, troubleshoot distributed systems, and participate in on-call and incident response while partnering across infrastructure teams.
NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling, and operational systems that make GPU clusters reliable, scalable, and safe to run. This role is part of a production engineering team focused on Kubernetes-based infrastructure, GPU cluster operations, reliability, automation, GitOps, and Day 2 operability across DGX Cloud environments.
What you’ll be doing:
- Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) and on-prem environments.
- Develop tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations.
- Improve Day 0 / Day 1 / Day 2 workflows for cluster bringup, handoff, and production operations.
- Reduce manual production touches through APIs, GitOps, automation, and agent-assisted workflows.
- Participate in on-call, incident response, debugging, and durable follow-up work.
- Partner with platform, storage, networking, security, and workload teams to make infrastructure production-ready.
What we need to see:
- 8+ years of experience building or operating production infrastructure.
- Strong programming skills in Python, Go, or similar.
- Experience with Linux, Kubernetes, containers, cloud infrastructure, or infrastructure automation.
- Ability to troubleshoot distributed systems in production.
- Clear communication and ability to work across teams.
- BS/MS in Computer Science or equivalent experience.
Ways to stand out from the crowd:
- Experience with GPU infrastructure, Kubernetes operators, GitOps, Terraform, ArgoCD, or fleet automation.
- Experience with SLOs, on-call, incident response, observability, and reliability practices.
- Exposure to BMaaS, VMaaS, managed Kubernetes, or multi-cloud infrastructure.
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hard-working people on the planet working for us. If you're creative, hard-working and self-motivated, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.NVIDIA Santa Clara, California, USA Office
2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara
NVIDIA San Francisco, California, USA Office
San Francisco, United States
NVIDIA San Jose, California, USA Office
San Jose, United States
Similar Jobs
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Senior Production Engineer will scale AI infrastructure, manage production systems, implement monitoring capabilities, and ensure reliability and performance across NVIDIA's AI clusters.
Top Skills:
Bright Cluster ManagerGoKubernetesPythonSlurm
.png)
Consumer Web • eCommerce • Machine Learning • Software • Sports • Analytics
Owns the end-to-end promotional lifecycle across digital and eCommerce platforms, including campaign planning, promotional calendar management, customer segmentation, execution, performance analysis, A/B testing, and optimization. Partners with marketing, CRM, legal, business operations, and analytics teams to measure incrementality, improve promotional effectiveness, and build scalable frameworks. This senior individual contributor also contributes to long-term growth and retention strategy.
Top Skills:
A/B TestingBrazeContent Management SystemsCrm PlatformsIterablePromotions EngineTalon.One
Information Technology • Productivity • Software • Infrastructure as a Service (IaaS)
Build backend-focused Java/Kotlin APIs and data-driven product features, while contributing to React dashboards and workflows. Design scalable systems, participate in architecture and code reviews, troubleshoot production issues using observability tools, and collaborate with data, reporting, design, and product teams to launch emerging products.
Top Skills:
Ai ToolingDistributed SystemsFront-End Testing FrameworksGraphQLGrpcJavaJavaScriptKotlinReactRelational DatabasesRestSQLStreaming Data
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
