Skills this job asks for
LeadershipMachine learningLLMs
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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✓
What Nvidia Corporation paid sponsored hires in similar roles113 certified filings for “Manager Systems Software” (Architectural and Engineering Managers) in CA: $214k–$248k, median $222k.
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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
- 113 certified filings for “Manager Systems Software” (Architectural and Engineering Managers) in CA: $214k–$248k, median $222k. Most were filed at wage level II (40%) — 2 lottery entries, ≈31% 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
Do you want to help the world build custom AI at scale? We’re hiring a founding Director to build and lead NVIDIA’s Forward Deployed Engineering organization for open models, including NVIDIA Nemotron and NVIDIA Cosmos, across North America. The mission is to turn open models into production-ready AI tuned to a specific domain, delivered through our partner ecosystem. We want any organization to build, own, and run its own AI on open source models, and this organization helps the ecosystem get there!
Unlike most forward deployed organizations, ours works primarily through NVIDIA’s partner ecosystem. Our FDEs work side by side with top partner engineering and research teams, co-lead joint customer engagements, and build the recipes and playbooks that help partners succeed and scale. This leader sets the strategy for North America, builds the organization, and carries the vision to partners, customers, and NVIDIA leadership. Are you an exceptional technical leader with deep roots in open model post-training and agent harness engineering, ready to build a world-class FDE organization? We’d love to meet you.
What you’ll be doing:
• This role sets the strategy and leads the team that delivers custom AI to end customers through NVIDIA’s partner ecosystem. The team deepens partner relationships and leads three-way engagements among NVIDIA, the partner, and the end customer. Our goal is hundreds of end customers running domain-specific Nemotron or Cosmos in production, supported by a strong ecosystem that delivers it.
• Hire and develop FDE leads, managers, and senior engineers across North America, and set a high bar for technical depth and customer impact. Create clear paths for growth and a team structure that scales with the ecosystem.
• The work stays technical. Set the technical direction for post-training, evaluation, harness engineering, and inference optimization, and be the person the team turns to on the hardest engagements. Keep up with the open model, post-training, and agents landscape, and bring new use cases and partner opportunities forward before partners ask.
• Partners are how we reach customers at scale. Build trusted relationships with leaders at partner and end-customer companies, shape joint plans and agreements, and see three-way engagements through to production. Set clear goals and track the results: partners adopting Nemotron, customers running in production, and customers willing to speak publicly. We help partners succeed on their own with reusable recipes, reference pipelines, and playbooks, so more developers can build domain-specific AI.
• We connect NVIDIA’s model research to partner and customer use cases. Work with Product, Research, and Engineering to bring what we see in the field back into Nemotron, Cosmos, and our software stack, and share what works with FDE leaders in other regions. Align priorities and resources with sales, partner, and solutions leaders, keep senior leadership informed on progress, and speak on NVIDIA domain-specific open models.
• Above all, we’re excited to help organizations worldwide build, own, and run their own AI on open source models!
What we need to see:
• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related field, or equivalent experience.
• 14+ overall years in ML or software engineering, applied AI, FDE, or solutions architecture, including 8+ years leading technical teams and 5+ years of hands-on LLM post-training with models taken to production.
• A track record of building and scaling technical organizations across multiple locations and time zones, including managing managers or leads, and setting goals and measuring results for a customer-facing technical team.
• Deep technical credibility in post-training (L
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