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Salary
$152k – $242k per year
Location
In office (Santa Clara, United States)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
NVIDIA is an American technology company founded in 1993 that invented the graphics processing unit and has become the dominant supplier of accelerated computing platforms for artificial intelligence. Its portfolio spans data centre GPUs and systems built on the Hopper and Blackwell architectures, GeForce consumer graphics, automotive and robotics platforms, high-speed networking acquired with Mellanox, and the CUDA software stack that binds the ecosystem together. Headquartered in Santa Clara, California, the company sells to cloud providers, enterprises, research institutions and gamers worldwide and is one of the most valuable listed businesses on the Nasdaq.

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPUs act as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent.

As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is encouraged to do their best work. NVIDIA is widely recognized as one of the most desirable employers, with some of the most versatile people in the world working for us. If you're passionate about building reliable systems software for cloud-scale GPU infrastructure, we encourage you to contribute to our team. We are looking for a Senior Software Engineer to join our DGX Cloud / Fleet Intelligence team and build agent-side systems that collect GPU health, host telemetry, inventory, attestation evidence, and BMC data across NVIDIA’s GPU fleet. This role includes contributing to open source software used by developers, operators, and customers working with NVIDIA GPU infrastructure.

What You'll Be Doing:

This role focuses on Fleet Intelligence in-band agent and out-of-band collector systems used for GPU health monitoring, host and BMC telemetry, inventory, attestation, diagnostics, and cloud operations automation, you will:

  • Design and develop Fleet Intelligence agent software that runs on Linux hosts, bare metal systems, and Kubernetes GPU nodes.

  • Build telemetry and health collection for NVIDIA GPUs, DCGM/NVML, drivers, CUDA runtime, InfiniBand, containers, kernel/OS state, CPU, memory, disk, and networking.

  • Develop inventory, enrollment, node identity, local state, attestation, and backend export workflows and maintain local API, Prometheus metrics, file export, and OTLP/HTTP export paths.

  • Build and improve Kubernetes daemonset deployment, systemd service packaging, .deb/.rpm packaging, and container image workflows.

  • Contribute to open source Fleet Intelligence agent and collector software, including code, tests, documentation, release artifacts, and community-facing engineering practices.

  • Contribute to out-of-band collection using Redfish/BMC interfaces for inventory, GPU attestation, BMC metrics, and logs.

  • Improve collector concurrency, rate limiting, retry behavior, credential handling, partial-failure handling, and backend submission semantics.

  • Collaborate with backend, infrastructure, SRE, security, and datacenter operations teams to deliver reliable GPU fleet observability.

What We Need To See:

  • 5+ years of industry software engineering experience with a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.

  • Strong Go development experience for Linux services, CLIs, agents, or daemons.

  • Rust experience, or strong willingness to work in Rust, for out-of-band collector development.

  • Strong Linux systems knowledge, including processes, filesystems, networking, service lifecycle, logs, permissions, and host diagnostics.

  • Experience with telemetry, observability, health monitoring, or fleet-management systems and with Docker, Kubernetes, Helm, and production deployment workflows.

  • Experience contributing to open source projects or working in public repositories with code review, issue tracking, documentation, release notes, and signed commits.

  • Familiarity with secure credential handling, enrollment flows, tokens/JWTs, and service-to-service authentication.

  • Strong debugging skills across hardware-adjacent software, operating systems, containers, and distributed backend integrations.

Ways To Stand Out From The Crowd:

  • Background with NVIDIA datacenter GPUs, DGX systems, DCGM, NVML, CUDA, GPU drivers, XID/SXID events, or GPU diagnostics.

  • Experience building host agents, node agents, collectors, monitoring daemons, or Kubernetes daemonsets.

  • Background with Redfish, BMCs, firmware inventory, secure boot state, PCIe device inventory, or hardware attestation.

  • Experience with OpenTelemetry, Prometheus, OTLP gateways, or metric/log export pipelines and operating software in AI, HPC, cloud, or large-scale datacenter environments.

  • Track record of meaningful open source contributions in systems software, observability, Kubernetes, Linux, hardware telemetry, Rust, or Go ecosystems.

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 August 28, 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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