Software Engineer, SRE and Production Engineering - DGX Cloud

at Nvidia

USD 184,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Communication @ 6 Debugging @ 4 GPU @ 4 Go @ 7 IaaS InfiniBand @ 6 Kubernetes @ 6 Linux @ 4 NVLink @ 6 Networking @ 6 Observability @ 4 Python @ 7 SRE @ 4

Details

NVIDIA DGX Cloud builds and operates large-scale GPU infrastructure for AI workloads. The team is seeking Software Engineers with SRE or Production Engineering experience who have worked hands-on with bare-metal NVIDIA systems. The role focuses on building software and operational tooling that moves GPU capacity from installed hardware to production service in an IaaS production environment supporting BMaaS and VMaaS.

The opportunity involves developing innovative technology to advance AI computing and make next-generation AI infrastructure production-ready at scale.

Responsibilities

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, and turn recurring issues into automated detection and repair.
Define validation and handoff criteria so new capacity enters production safely and consistently.
Participate in on-call duties, incident response, and 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.

Requirements

8+ years of experience 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 through 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 spanning multiple teams.
BS or MS in Computer Science, or equivalent experience in a related field.

Preferred Qualifications

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.

Compensation and Benefits

Base salary range: USD 184,000–287,500 per year.
Eligibility 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 is an equal opportunity employer.