Jobs / United States / Nvidia Corporation
Senior Software Safety Engineer, Halos - Autonomous Vehicles
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 roles701 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).
- 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).
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.
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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
NVIDIA is widely regarded as a leading company in technology. It has groundbreaking developments in High-Performance Computing, Artificial Intelligence, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work enables exploration of new universes, enables outstanding creativity and discoveries that were once science fiction from artificial intelligence to autonomous cars and robotics. NVIDIA Halos is the full-stack, comprehensive safety system that unifies autonomous machines architecture, AI models, chips, software, tools, and services to ensure the safe development and deployment of Physical AI. We are actively seeking a Senior SW Safety Engineer to join the Halos team and collaborate closely with other teams across NVIDIA working on autonomous vehicle and robotics safety. What You’ll Be Doing: • Be pivotal in ensuring the safety of our AI-based autonomous system software. • Engage with a diverse team of engineers across the entire DRIVE platform and related research unit. You will work closely with the groups handling automotive functional safety and safety of the intended functionality. • Collaborate with the teams dedicated to robotics, humanoids, industry safety and other safety critical applications across NVIDIA. • Apply your skills to guide the teams to specify, build, implement, and verify safety requirements across our software stack from drivers and acceleration libraries to AI-based technologies, including end-to-end models. • Help NVIDIA team implementing our Product Life Cycle to integrate the process principles of AI safety. • Your role includes engaging in customer interaction and international standardization activities related to safety of Artificial Intelligence. • Support system safety activities including decomposition of safety requirements, system and component level build analysis (FTA, DFA, CCF, FMEA, etc.), and architectural safety analysis across hardware and software boundaries. • Collaborate with external certification bodies, assessors, and regulators. You will present, defend, and justify safety arguments and evidence. This supports successful safety certification reviews related to functionality and AI. What we need to see: • BS, MS, or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or related technical field, or equivalent experience. • 12+ years of shown experience in Artificial Intelligence and SW safety related processes, methodologies, tools. • Experience in AI safety methods and tools (adaptability testing, uncertainty evaluation, out of distribution detection, and other related methods). • Familiarity with system software development and embedded platforms. • Strong written and verbal communication skills. • Experience in reviewing existing processes and finding gaps to suggest improvements. • Experience producing safety plans, safety analyses reports, safety case documentation, and evidence packets in support of safety certification and audit activities. Ways to Stand Out from the Crowd: • Strong background in safety standards (ISO PAS 8800, ISO/IEC TR 5469, ISO 21448, ISO 26262, IEC 61508). • Background in system safety methodologies & practices (HARA, FMEA, FTA, STPA). • Hands-on experience with innovative systems engineering methodologies – such as requirements management, peer review processes, configuration management, requirements management in an agile development environment, risk management, requirements verification and traceability, validation and verification, and architectural decomposition. • Hands-on experience in autonomous systems. • Success applying the V-Model to sophisticated AI-based engineering projects, ideally in all stages of