Jobs / United States / Nvidia Corporation

Nvidia Corporation

Senior Technical Program Manager, OEM Enablement

2 Locations Posted today

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Skills this job asks for

Deep learningLeadershipAccount managementSupply chain

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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 roles3 certified filings for “Technical Program Manager” (Information Technology Project Managers) in WA: $168k–$192k, median $184k.
  • 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
3 certified filings for “Technical Program Manager” (Information Technology Project Managers) in WA: $168k–$192k, median $184k. Most were filed at wage level IV (100%) — 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

At NVIDIA, we're at the forefront of innovation, redefining the future of computing with our powerful GPU technology. Our GPUs serve as the brains behind computers, robots, and self-driving cars, enabling them to understand and interact with their surroundings. NVIDIA is seeking a Senior Technical Program Manager on the Solutions Architecture team to help our OEM ecosystem and customers build, deploy, and support successful AI Factories. Academic and commercial groups worldwide use NVIDIA products to advance deep learning, data analytics, and accelerated computing. Join the team building many of the world's largest and fastest data centers and supercomputers! You will work across OEM partners and NVIDIA teams to identify technical and ecosystem gaps and turn them into programs that improve customer outcomes. This role requires technical depth, adaptability, and an understanding of the end-to-end lifecycle of hardware systems in an AI Factory, from development and integration through deployment, operations, and support. You will work closely with engineering to solve problems while building relationships and influencing decisions across partner organizations and leadership teams. As products, customer needs, and the ecosystem evolve, you will help define where technical program leadership can have the greatest impact. What you will be doing: • Lead technical programs across AI Factory development, deployment, and support, working with engineering and OEM partners to close readiness gaps and resolve dependencies as customer needs evolve. • Work across NVIDIA Solutions Architects (SAs), Field Application Engineers (FAEs), sales and account management, and engineering functions to align technical requirements, partner capabilities, and customer expectations. • Assess how OEM services and support capabilities meet CSP and NCP customer needs, and develop programs to close gaps. Areas may include technical training, engineering support, NVIDIA product knowledge and debugging, return material authorization (RMA), spares, and service readiness. • Engage OEM engineering, supply chain, and support teams to understand challenges, shape joint plans, and resolve technical issues with NVIDIA experts. Coordinate targeted training and knowledge transfer with SAs, FAEs, and engineering to strengthen OEM capabilities. • Engage OEM and NVIDIA leadership to frame opportunities, communicate technical and business implications, and influence decisions. Establish clear ownership and milestones; standardize templates, trackers, dashboards, and reviews for partner programs, deployment services, and leadership updates. • Use field operations data, customer and partner feedback, and engineering findings to improve partner workflows, deployment execution, and operating processes. Turn lessons learned into repeatable improvements in products, tooling, OEM training, and lifecycle support. What we need to see: • Bachelor's degree in Electrical Engineering, Computer Science, Information Technology, or a related technical field, or equivalent experience. • 12+ years of overall experience in enterprise and/or hyperscale data centers, hardware systems, or related infrastructure, with experience leading cross-functional technical programs. • Understand the hardware systems lifecycle—from development and validation through deployment and support—in large-scale AI infrastructure. • Technical depth to work closely with engineering on NVIDIA or similar AI systems, understand product architecture and system dependencies, and drive debugging and issue resolution with technical experts. • Bring structure to ambiguous problems, establish ownership and measurable outcomes, and adapt priorities as technologies and customer needs evolve. • Strong communication an

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