NVIDIA Logo

NVIDIA

Senior Production Engineer - DGX Cloud

Posted Yesterday
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Santa Clara, CA, USA
184K-357K Annually
Senior level
In-Office or Remote
Hiring Remotely in Santa Clara, CA, USA
184K-357K Annually
Senior level
Build and operate reliable, scalable production software, automation, and infrastructure for NVIDIA DGX Cloud AI inference and agentic workloads. Responsibilities include Kubernetes and multi-cloud deployments, infrastructure as code, GitOps, observability, SLI/SLO definition, capacity management, incident response, safe rollouts, recovery automation, and reducing operational toil. The role collaborates across platform, networking, storage, security, model, and GPU infrastructure teams.
The summary above was generated by AI

NVIDIA DGX Cloud delivers AI services and endpoints for research and production workloads. We are looking for a Senior Production Engineer to build software and automation that make those services reliable, scalable, and safe to operate. The Production Engineering team works on large-scale distributed systems spanning internal and external model endpoints; regional control plane services that orchestrate workloads and route requests; and the GPU/CPU compute infrastructure where inference and agentic workloads run. Our work spans Kubernetes clusters across AWS, Azure, Google Cloud, other partner cloud environments, and on-premises deployments.
What you’ll be doing:

  • Build and operate production software, automation, and tooling for control plane services, model deployments, and inference and agentic workloads across DGX Cloud environments.
  • Improve the reliability of inference and agentic platforms and services, including NVIDIA Cloud Functions, SGLang- and vLLM-based endpoints, and inference services built with NVIDIA Dynamo, through health validation, safer rollouts, observability, and recovery.
  • Improve endpoint availability, inference routing, capacity management, and service health to maintain predictable performance as workloads and demand change.
  • Use infrastructure as code and GitOps to deploy, configure, validate, upgrade, and recover services consistently across environments.
  • Build workflows for service enablement, model releases, handoff, deprecation, and ongoing operations; replace repeatable manual work with reliable automation.
  • Define and instrument SLIs and SLOs for inference and control plane services, including availability and latency, use error budgets to guide reliability improvements, and make production health visible to partner teams.
  • Participate in on-call and incident response, troubleshoot failures across routing, model runtimes, software, and infrastructure, and turn recurring issues into automation and durable fixes.
  • Collaborate with model, platform, storage, networking, security, and GPU infrastructure teams to design and operate services safely at scale.

What we need to see:

  • 8+ years of experience building or operating production services and large-scale distributed systems, including hands-on automation.
  • Strong programming skills in Python, Go, or a comparable language, with experience developing tools for production operations.
  • Experience with infrastructure as code, configuration management, or GitOps, and with building automation for repeatable service deployments and changes.
  • Strong knowledge of Linux, Kubernetes, containers, cloud infrastructure, distributed systems, and networking fundamentals; ability to diagnose failures in production.
  • Understanding of SRE principles, including SLIs, SLOs, error budgets, incident response, and reducing operational toil.
  • Experience instrumenting services and using metrics, logs, and traces to understand system behavior and improve reliability.
  • Clear technical communication and ability to work across engineering teams.
  • BS/MS in Computer Science or equivalent experience.

Ways to stand out from the crowd

  • Familiarity with technologies such as vLLM, SGLang, PyTorch, TensorRT-LLM, NVIDIA Dynamo, CUDA, or NCCL, and with GPU performance analysis.
  • Experience building Kubernetes operators, controllers, workload orchestration services, fleet management systems, or self-healing automation.
  • Experience with Terraform, Argo CD, CI/CD, policy validation, or safe deployment and rollback systems.
  • Experience developing with AI tools and agents.
  • Background with production AI inference or agentic workloads, including debugging issues across models, runtimes, Kubernetes, and hardware.


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.

Applications for this job will be accepted at least until October 6, 2026.

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.

HQ

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

4 Days Ago
In-Office or Remote
2 Locations
152K-288K Annually
Senior level
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Build and operate software automation for large-scale NVIDIA GPU infrastructure. Responsibilities include bare-metal provisioning, hardware validation, firmware and software upgrades, cluster lifecycle management, BMC and Redfish tooling, failure diagnosis, observability, incident response, and automated repair. The role supports NVL72 systems, BlueField DPUs, Linux, Kubernetes, and cloud or on-premises environments while coordinating across hardware, networking, platform, data center, and partner teams.
Top Skills: Argo CdBluefield-3 DpusBmcDriver ManagementFirmware ManagementGitopsGoInfinibandKubernetesLinuxNetwork BootNvidia Nvl72NvlinkPythonRedfishSlosSpectrum-X
11 Days Ago
In-Office or Remote
Santa Clara, CA, USA
184K-357K Annually
Senior level
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
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.
Top Skills: APIsArgocdBmaasCloud InfrastructureContainersGitopsGoGpu InfrastructureKubernetesKubernetes OperatorsLinuxManaged KubernetesMonitoringMulti-Cloud InfrastructureObservabilityPythonTerraformVmaas
One Month Ago
In-Office or Remote
Santa Clara, CA, USA
176K-334K Annually
Senior level
176K-334K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Design, implement, and operate large-scale, high-performance storage clusters for AI/ML workloads. Develop monitoring, alerting, automation, and capacity management. Optimize latency, throughput, caching, compression, deduplication, tiering, and data placement. Support lifecycle from design to production, participate in on-call rotations, incident response, and continuous improvement with AI-driven automation and predictive analytics.
Top Skills: AnsibleBashBlock StorageCC++ChefCi/CdClustered File SystemsContainersDistributed StorageElastic StackFibre ChannelFile StorageGitGoGrafanaInfluxdbIscsiJavaKubernetesLinuxNfsNode.jsNvme Over FabricsObject StorageOpenstackParallel File SystemsPrometheusPuppetPythonRdmaS3SmbTerraformVirtualization

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

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account