hirly

NVIDIA

Software Engineer, SRE and Production Engineering - DGX Cloud

US, CA, Santa Clara · US, TX, Remote · US, VA, Remote · US, SD, Remote · US, UT, Remote · US, SC, Remote

See how you match this job — and similar ones. Free.

Upload your resume and hirly scores it against this role at NVIDIA first, then against similar open jobs, and shows where you fit and why.

PDF or DOCX, up to 12MB. No sign-up to see your matches.

Get past the screening software and onto a recruiter's desk

hirly rewrites your resume for this job — matching the keywords and skills in the posting, moving your most relevant experience to the top, and writing a cover letter to fit. About 30 seconds.

  • Keywords matched to this posting
  • Fit score before you apply
  • Cover letter included
Tailor my resume for this job →

Apply from your AI assistant

Connect hirly to Claude and ask it to apply to this job. hirly tailors your resume, fills the employer’s form and asks before sending. ChatGPT: manual setup today.

Some employer sites stop an application at a CAPTCHA or sign-in and hand it back with a link. Applying needs a paid plan. Works with any assistant that supports MCP.

hirly's read of this role

Role family
Engineering
Seniority
Mid level
Country
US
Work mode
On-site / unstated
First seen by hirly
10 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

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.

Original posting on NVIDIA's site ↗

Listed on hirly, a job board. hirly is not the employer: NVIDIA is hiring for this role.

Browse similar roles

Want this one?

Upload your resume and hirly rewrites it for this job and writes the cover letter — in about thirty seconds, before you sign up.

Tailor my resume for this job