Jobs / United States / Nvidia Corporation

Nvidia Corporation

Senior Systems Software Engineer, GPU Fleet Telemetry

3 Locations Posted today

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Skills this job asks for

Inventory managementLinuxKubernetesNetworkingRustDocker

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Nvidia Corporation paid sponsored hires in similar roles701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Nvidia Corporation paid sponsored hires in similar roles
701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k. Most were filed at wage level IV (82%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

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 diagnostic

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