Jobs / United States / Nvidia Corporation
PhD Research Intern, Architecture – 2027
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 roles83 certified filings for “Research Scientist” (Computer and Information Research Scientists) in CA: $164k–$201k, median $169k. Most were filed at wage level II (45%) — 2 lottery entries, ≈31% 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
The NVIDIA Architecture Research Group is seeking an intern to help define the future of GPU and data-center computing. Our research spans GPU microarchitecture, memory systems and memory models, large-scale data-center hardware, emerging accelerators, and the architecture implications of new workloads in AI, scientific computing, robotics, and other rapidly evolving domains. Are you excited about exploring foundational research questions, developing new architectural ideas, and helping translate those ideas into future NVIDIA systems? In this position, you will apply your knowledge of computer architecture, parallel computing, compilers, runtime systems, and workloads to explore new hardware and hardware–software co-design opportunities. You will work with researchers and product architects to formulate research questions, develop and evaluate architecture concepts, and build the models, simulators, prototypes, and experimental infrastructure needed to test them. Projects may range from mechanisms within a GPU to memory consistency and programmability, rack- and data-center-scale architectures, and specialized hardware for emerging applications. You should have a strong foundation in computer architecture and parallel systems, an ability to work across hardware and software boundaries, and experience with some combination of architecture modeling, simulation, workload analysis, compilers, runtime systems, or CPU/GPU programming. You should also be comfortable building robust research prototypes and communicating the insights produced by your work. NVIDIA pioneered programmable GPUs and CUDA and continues to shape the future of accelerated computing. This position offers an opportunity to conduct ambitious research and have a direct impact on future products. What you’ll be doing: • Investigate new architecture concepts for future GPUs, memory systems, accelerators, and data-center-scale computing platforms. • Study emerging workloads and identify the architectural bottlenecks and opportunities they create. • Explore hardware–software co-design across architecture, compilers, runtime systems, programming models, and applications. • Develop models, simulators, prototypes, and experimental tools to evaluate new architecture ideas. • Research new approaches to memory hierarchy, coherence, consistency, data movement, and system-level programmability. • Collaborate with NVIDIA researchers, GPU architects, software teams, and product groups to develop and evaluate promising concepts. • Clearly communicate research findings through presentations, technical reports, and potentially research publications. • Help transfer successful research ideas, methodologies, and tools into NVIDIA product teams. What we need to see: • Pursuing PhD Degree in relevant discipline(s) (CS, CE, EE, Physics, Math). • Relevant industrial and University experience. Relevant industries include hardware, software, and algorithm development in PC or workstation graphics, digital video or image processing, video game or console, cell phones or consumer electronics, rendering software, and computing. • Strong programming ability in C/C++, and scripting languages. • Experience as a CUDA programmer. • Background with building computer system simulators. • Experience building efficient low-level software tools such as runtime systems, binary translators, or compilers. • Strong background in computer architecture and parallel computer architectures. Ways to stand out from the crowd: • Prior research experience and/or research publications at ISCA/MICRO/ASPLOS/HPCA/MLSYS • Versatile in using generative AI coding tools • Versatile in using GPU profiling tools and running DL models on GPUs NVIDIA is widely considered to be one of the technology world