Jobs / United States / Nvidia Corporation
Senior Technical Product Manager, Infrastructure Resilience
Nvidia Corporation · 🇺🇸 2 Locations
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. USCIS also records 394 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- 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. 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 roles7 certified filings for “Product Manager” (Marketing Managers) in CA: $180k–$217k, median $201k. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
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).
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Sponsor Radar — Nvidia Corporation
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. USCIS also records 394 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Nvidia Corporation →
About the role
We're building software that helps cloud partners and operators understand why AI workloads fail and keep GPU clusters ready for work. You'll bring deep experience in GPU cluster operations to help automate investigations across hardware and software. Working with engineering and operations teams, you'll turn those findings into product priorities. We're hiring a Technical Product Manager to own AI infrastructure resilience platform capabilities and developer experience, including GPU node health contracts and interfaces, workload failure attribution, and the open-source software that operators and cloud partners build on. You will own the roadmap and work directly with the engineering and operations communities that deploy and extend this software. This role contributes to NVIDIA's open, modular infrastructure software for designing, operating, and optimizing AI factories at scale. We encourage technical product managers, architects, site reliability engineers, and infrastructure engineers who understand the management of GPU clusters and want to help operators solve these problems to apply. What you'll be doing: • Own the product vision, roadmap, and delivery priorities for AI infrastructure resilience, partnering with engineering on architecture and execution. • Work with customers and partners to identify gaps in GPU cluster operations and define platform capabilities that address them. Help operators assess node readiness and distinguish hardware failures from application failures, while shaping which signals are available through public interfaces or extensions that require additional access. • Work directly with cloud partners and cluster operators to translate their operational requirements into platform capabilities. • Lead community engagement for open-source platform projects, including contribution models, ecosystem partnerships, and developer adoption. What we need to see: • 12+ years of experience across product management, solutions architecture, software engineering, or site reliability engineering on technical infrastructure products. Technical depth in GPU or AI infrastructure is required. • Knowledge of GPU failure modes: XID codes, ECC correctable and uncorrectable errors, DCGM metrics, NVLink and PCIe health signals. • Understanding of why AI workloads fail and GPU nodes become unavailable for scheduling. This includes distributed training failures (NCCL timeouts and framework errors), distinguishing hardware from application faults, scheduler health and drain behavior, and interpreting signals from DCGM, sysfs, and dmesg. • Demonstrated ability to work with senior technical customers and translate operational requirements into product decisions. • Strong written and verbal communication across technical and non-technical audiences. • Bachelor's degree in Computer Science or equivalent experience. Ways to stand out from the crowd: • Hands-on experience as a site reliability or infrastructure engineer supporting GPU clusters. You have triaged workload failures, interpreted XID logs, and worked across teams to investigate failed training runs spanning thousands of GPUs. • Deep familiarity with GPU scheduling, topology-aware placement, or multi-tenant GPU cluster management: Slurm prolog/epilog, Kueue, or Kubernetes-native scheduler environments. • Experience building products that produce structured diagnostics or attribution output: health verdict schemas, log analysis pipelines, rules-engine systems, or observability APIs at data center scale. • Practical experience delivering or contributing to an open-source infrastructure project, including managing contributor engagement on GitHub. Known throughout the tech industry as a highly sought-after employer, NVIDIA delivers highly competitive sa