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Software Engineer, SRE and Production Engineering - DGX Cloud

Role overview

Qualifications

  • 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
  • BS/MS in Computer Science or equivalent experience in a related field
  • Direct experience working with BMC and Redfish for server provisioning, health inspection, power control, or fault diagnosis

Responsibilities

  • Build automation for bare-metal provisioning, hardware validation, firmware and software upgrades, repair, and cluster lifecycle management
  • Manage and enhance NVIDIA NVL72 systems and BlueField-3 or later DPUs within cloud partner and on-premises environments
  • 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

Key facts

Hard skills

Other skills

  • Communication
  • Collaboration
  • Problem Solving

About the company

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NVIDIA

Semiconductors

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

Company details

Company typeXLarge
IndustrySemiconductors
Company size10001

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Job description

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.
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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 13, 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.

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