Jobs / United States / Nvidia Corporation
Senior Software Engineer, Test Engineering
Nvidia Corporation · 🇺🇸 3 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 roles31 certified filings for “Engineer Senior SWQA Test Developer” (Software Quality Assurance Analysts and Testers) in CA: $164k–$201k, median $201k. 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 at the forefront of groundbreaking advances in artificial intelligence, high-performance computing, and simulation. The company is widely recognized as one of the technology industry's most desirable employers. We are looking for a Senior Software Engineer to join the Test Engineering team for NVIDIA Driver Assistance Systems (NDAS). In this role, you will help build and scale simulation and validation pipelines for advanced driver assistance systems. Your work will span data mining, automated labeling, benchmarking, CI/CD infrastructure, AI-assisted workflows, and large-scale test automation. Close collaboration with machine learning engineers, software developers, and systems engineers shapes the tools, datasets, metrics, and processes needed to evaluate complex autonomous driving systems. What you'll be doing: • Test Case Engineering: Design, curate, and maintain comprehensive test suites covering system requirements, edge cases, and failure modes across diverse road types, environmental conditions, and vehicle interactions. • Tooling and Metrics Development: Architect and implement scalable evaluation tools and metrics that support critical system testing, verification, and release decisions. • AI-Assisted Data Pipelines: Build ground-truth datasets for ADAS features and develop LLM- and VLM-powered auto-labeling solutions that accelerate and scale data annotation workflows. • Simulation and Validation Infrastructure: Develop and improve simulation, replay testing, benchmarking, and CI/CD pipelines for efficient, repeatable, and large-scale validation. • Process Scaling: Create and refine standard operating procedures, labeling guidelines, and quality-control mechanisms, enabling established workflows to scale across internal and external labeling teams. • Issue Triage and Resolution: Identify, reproduce, and debug system anomalies. Collaborate closely with cross-functional teams to determine root causes, drive timely resolution, and validate software fixes. • Test Execution and Analytics: Execute offline validation using internal test frameworks, analyze large and complex datasets, and produce reports with actionable insights that guide system improvements. • Safety and Compliance: Ensure validation activities follow applicable automotive safety standards, regulatory requirements, and industry best practices. What we need to see: • Master's degree or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related technical field, or equivalent practical experience. • 6+ years of hands-on experience in software development, testing, validation, or quality engineering, ideally in autonomous driving, automotive systems, robotics, or another safety-critical domain. • Hands-on background in ADAS or autonomous driving systems, covering simulation, replay-based testing, and model-based development workflows. • Strong programming and scripting skills in Python, C++, and Shell. • Fluency with modern software testing practices, including unit, integration, system, and end-to-end testing. • Experience designing or maintaining automated testing, benchmarking, or CI/CD infrastructure. • Familiarity with modern AI technologies—including LLMs, VLMs, and AI agents—and a track record applying them to workflow automation, data labeling, or engineering productivity. • Strong analytical, debugging, and problem-solving skills, with the ability to work effectively across multiple engineering disciplines. Ways to stand out from the crowd: • A strong automation mindset and a track record of building software, platforms, or internal tools that significantly improve engineering efficiency and scalability. • Hands-on work with data science methodologies, large-scale data analysis, and advanced SQL