Senior Software Engineer, Bare Metal Infrastructure – DGX Cloud

Posted 8 Hours Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Build and maintain production software for bare-metal GPU infrastructure across provisioning, hardware validation, firmware management, auditing, remediation, and production handoff. Integrate Redfish and vendor BMC interfaces, automate failure detection and recovery, debug issues spanning hardware, firmware, Linux, networking, and provisioning, and collaborate with vendors and infrastructure teams. The role also uses AI agents and LLM tools extensively for software development, testing, code review, and failure investigation.
Summary Generated by Built In

NVIDIA DGX Cloud builds large-scale GPU infrastructure that powers the world’s most demanding AI workloads. Our Bare Metal Infrastructure team owns the software that turns newly racked hardware into reliable, validated production capacity. We’re looking for a software engineer with deep systems engineering instincts — someone who writes production code and understands how servers, firmware, BMCs, and networks actually behave. You’ll work across the full bare-metal lifecycle: new platform introduction, firmware qualification, automated provisioning, validation, remediation, and handoff to production. We use AI agents and LLM tools heavily in how we build software, and we want someone excited to push that further.


What you’ll be doing:

  • Designing, building, and maintaining production services for bare-metal discovery, provisioning, hardware validation, firmware upgrades, auditing, and repair across large GPU fleets.
  • Developing integrations with Redfish and vendor BMC interfaces to manage server state, collect inventory and health data, enforce configuration, and drive recovery — handling vendor differences in code.
  • Contributing to and reviewing code in our Rust codebase, and building supporting tools and services in Go and Python.
  • Turning recurring hardware, firmware, and connectivity failures into automated detection, validation, and repair workflows.
  • Defining and implementing automated validation and handoff criteria for new platforms, firmware releases, and rack-scale deployments.
  • Debugging complex failures across hardware, firmware, Linux, networking, and provisioning services, and feeding what you learn back into the software.
  • Partnering with server and component vendors and with internal platform, networking, datacenter, and production engineering teams to resolve cross-boundary issues.
  • Using AI agents and LLM tools daily to write, review, and test code and to investigate failures, and helping shape how the team builds with AI.

What we need to see:

  • BS or MS in Computer Science, Computer Engineering, or equivalent experience.
  • 5+ years building production infrastructure software, automation, or services, including substantial hands-on work with bare-metal server systems.
  • Strong programming skills in Rust, Go, or Python, with a track record of designing, testing, shipping, and maintaining production code and willingness to work in Rust regularly.
  • Deep knowledge of enterprise server hardware from multiple vendors (Dell, Supermicro, Lenovo, HPE), including BMCs, BIOS/UEFI, and firmware management.
  • Direct experience with Redfish and IPMI for provisioning, health inspection, power management, or fault diagnosis, and with network boot (PXE/iPXE, DHCP, HTTP boot).
  • Strong Linux knowledge: boot process, kernel and driver interactions, hardware discovery, and low-level failure analysis.
  • Solid datacenter networking fundamentals with the ability to trace connectivity problems across host, management, and infrastructure networks.
  • Demonstrated, regular use of AI agents and LLM tools in software development, with strong interest in improving and the judgment to validate what they produce.

Ways to stand out from the crowd:

  • Production experience writing Rust.
  • Experience with NVIDIA DGX or NVL72 systems, NVLink, InfiniBand, Spectrum-X, or BlueField DPUs.
  • Background in hardware qualification, rack-scale bring-up, firmware certification, or new product introduction, including safe, scalable workflows for fleet firmware upgrades, configuration enforcement, hardware replacement, and recovery.
  • Experience with Kubernetes, GitOps/Argo CD, or fleet-management platforms.
  • Examples of AI-driven tooling or workflows you’ve built that measurably changed how you or your team ships software.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 1, 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.

Skills Required

  • BS or MS in Computer Science, Computer Engineering, or equivalent experience
  • 5+ years building production infrastructure software, automation, or services, including substantial hands-on bare-metal server experience
  • Strong programming skills in Rust, Go, or Python, with experience designing, testing, shipping, and maintaining production code
  • Willingness to work regularly in Rust
  • Deep knowledge of enterprise server hardware from multiple vendors, including BMCs, BIOS/UEFI, and firmware management
  • Direct experience with Redfish and IPMI for provisioning, health inspection, power management, or fault diagnosis
  • Experience with network boot technologies including PXE, iPXE, DHCP, or HTTP boot
  • Strong Linux knowledge, including boot processes, kernel and driver interactions, hardware discovery, and low-level failure analysis
  • Solid datacenter networking fundamentals and ability to troubleshoot host, management, and infrastructure networks
  • Regular use of AI agents and LLM tools in software development, with ability to validate generated output
  • Production Rust experience
  • Experience with NVIDIA DGX or NVL72 systems, NVLink, InfiniBand, Spectrum-X, or BlueField DPUs
  • Experience in hardware qualification, rack-scale bring-up, firmware certification, new product introduction, fleet firmware upgrades, configuration enforcement, hardware replacement, or recovery
  • Experience with Kubernetes, GitOps, Argo CD, or fleet-management platforms
  • Examples of AI-driven tooling or workflows that measurably improved software delivery

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.

  • 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.
  • 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.
  • 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.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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