Jobs / United States / Nvidia Corporation

Nvidia Corporation

Lead User Experience Researcher - IT and Employee Productivity

US, CA, Santa Clara Posted today

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Skills this job asks for

LeadershipUX researchProduct managementSQLPythonLLMs

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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 roles1 certified filing for “IT Engineer” (Network and Computer Systems Administrators) in CA: $156k–$156k, median $156k.
  • 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
1 certified filing for “IT Engineer” (Network and Computer Systems Administrators) in CA: $156k–$156k, median $156k. 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

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we're tapping into the unlimited potential of AI to define the next era of computing. NVIDIA IT builds the products NVIDIANs use to get work done every day: the company intranet and mobile app, IT help and self-service, an AI personal assistant, and secure workspaces where employees run their own AI agents. We're hiring our first user experience researcher to answer a question that matters more every quarter: what makes people productive at NVIDIA, and what should we build, buy, or change so more people can work that way? This is a senior, independent role with a long horizon. Our users are our colleagues, so access is never the bottleneck. You start with rich data: an annual IT survey with thousands of written comments from employees in 36 countries, support tickets, and product analytics. You'll set the research agenda, run the studies that matter most, and raise the research bar for the product managers and designers you work with. What you'll be doing: • Own a multi-quarter research program on how NVIDIANs work: what separates people who have adopted new ways of working, including AI tools, from those who haven't, and which tools, built or bought, would help the rest. • Shape our core products. Find the fundamental changes that would make our intranet, IT help, and AI assistant more useful, starting from questions like "what does a typical work day at NVIDIA look like?" • Pair field research (contextual inquiry, interviews, diary studies) with survey, support, and analytics data. Use AI to scale analysis without trading away validity. • Bring rigor. Choose methods that hold up (reliability, validity, sampling), and help the team distinguish between decisions that benefit from research vs. decisions that can just be made. • Raise the team's research craft. Coach PMs and designers on study design, interview guides, and live interviewing, and partner with designers on usability work • Build the practice from zero: a participant panel, consent and confidentiality standards for research with colleagues (with HR and Legal), and an insights repository so research compounds instead of repeating. • Turn findings into decisions. Present clear recommendations to IT leadership, define experience and adoption metrics with PMs, and follow through until insights shape roadmaps, not just fixes. What we need to see: • 12+ years in UX research or a closely related field, including leading strategic, multi-quarter research programs. • Master's or PhD in Human-Computer Interaction, Psychology, Cognitive Science, Anthropology, Sociology, or a related field, or equivalent experience. • Deep mixed-methods expertise: generative field research, survey design and analysis (including open text), and analysis of behavioral data. • A portfolio or case studies showing research that changed strategy, roadmap, or investment decisions, not only feature details. • Experience researching enterprise, internal, or workplace products used by employees. • Proven ability to work as the first or only researcher on a team: set the agenda, say no to low-value studies, and coach others on research craft. • Clear writing and presentation that moves senior leaders to a decision. Ways to stand out from the crowd: • Research on AI tool adoption, knowledge-worker productivity, or how teams change the way they work. • Internal IT, employee experience, or workplace technology research. • Quantitative depth: SQL, R, or Python, and quasi-experimental designs (such as matched comparisons) that separate what drives adoption from what only correlates with it. • You've used LLMs to scale research synthesis and know where they fail. NVIDIA is wide

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