NVIDIA DGX Cloud builds and operates large-scale GPU infrastructure for AI workloads. We are looking for Software Engineers with SRE or Production Engineering experience who have worked hands-on with bare-metal NVIDIA systems. This team builds the software and operational tooling that moves GPU capacity from installed hardware to production service supporting an IaaS production environment of BMaaS, VMaaS.
What makes this opportunity outstanding is the chance to work with innovative technology to develop the future of AI computing. Join us to be part of a world-class team and make an impact on the next era of computing! At NVIDIA, you’ll help make next-generation AI infrastructure production-ready at scale!
What you’ll be doing:
- Build automation for bare-metal provisioning, hardware validation, firmware and software upgrades, repair, and cluster lifecycle management.
- Build tools using BMC and Redfish interfaces to assess hardware health, regulate server state, and facilitate recovery workflows.
- Manage and enhance NVIDIA NVL72 systems and BlueField-3 or later DPUs within cloud partner and on-premises environments.
- Diagnose failures across servers, DPUs, GPU systems, CPU systems, networking, Linux, and Kubernetes; turn recurring issues into automated detection and repair.
- Define validation and handoff criteria so new capacity enters production safely and consistently.
- Take part in on-call duties, incident response, root-cause analysis, and ensure permanent resolutions are implemented.
- Collaborate with hardware, networking, platform, data center operations, and partner teams to resolve issues across ownership boundaries.
What we need to see:
- 8+ years building software for or operating production infrastructure, including substantial hands-on bare-metal experience.
- Strong Go or Python skills, with a record of delivering production automation and services.
- Direct experience working with BMC and Redfish for server provisioning, health inspection, power control, or fault diagnosis.
- Practical experience working directly with NVIDIA GPU hardware, including NVL72 systems, and BlueField-3 or later DPUs.
- Experience with Linux, firmware and driver management, network boot, and the server lifecycle from initial provisioning through repair.
- Experience managing production reliability via on-call duties, incident handling, observability, and durable solutions.
- Ability to debug failures across hardware, host operating systems, networking, and distributed services.
- Clear communication and demonstrated ownership of problems that span multiple teams.
- BS/MS in Computer Science or equivalent experience in a related field.
Ways to stand out from the crowd:
- Experience operating BlueField DPUs in DPU mode, including host-to-DPU connectivity and lifecycle debugging, or equivalent experience.
- Background with NVLink, InfiniBand, Spectrum-X, or GPU cluster performance validation.
- Experience building safe, repeatable workflows for rack-scale bringup, firmware upgrades, hardware replacement, and customer handoff.
- Background with Kubernetes, GitOps, Argo CD, SLOs, and fleet-wide automation.
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.Skills Required
- 8+ years building software for or operating production infrastructure
- Substantial hands-on bare-metal experience
- Strong Go or Python programming skills
- Experience delivering production automation and services
- Direct experience with BMC and Redfish for server provisioning, health inspection, power control, or fault diagnosis
- Practical experience with NVIDIA GPU hardware, including NVL72 systems and BlueField-3 or later DPUs
- Experience with Linux, firmware and driver management, network boot, and server lifecycle management
- Experience with production reliability, on-call duties, incident handling, observability, and durable solutions
- Ability to debug failures across hardware, host operating systems, networking, and distributed services
- Clear communication and ownership of problems spanning multiple teams
- BS or MS in Computer Science or equivalent experience in a related field
- Experience operating BlueField DPUs in DPU mode, including host-to-DPU connectivity and lifecycle debugging
- Experience with NVLink, InfiniBand, Spectrum-X, or GPU cluster performance validation
- Experience building workflows for rack-scale bringup, firmware upgrades, hardware replacement, and customer handoff
- Experience with Kubernetes, GitOps, Argo CD, SLOs, and fleet-wide automation
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.
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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.
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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.
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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.”
