Computer Architecture Intern
About the job
- Must be actively enrolled in a university pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field for the full duration of the internship.
- The anticipated graduation date, including month and year, must be clearly indicated on a resume or CV.
- Course or internship experience related to the listed focus areas may be required, depending on the internship role.
- Experience in one or more of the following areas may be required: Computer Graphics, Deep Learning, Ray Tracing, Parallel Programming, Memory Architecture, or High-Performance Computing Systems.
- Knowledge or experience in Digital Systems, VLSI Design, GPU or CPU Architecture, Computer Arithmetic, CMOS Transistors and Circuits, Computer Organization, or Computer System Design may be required.
- Knowledge or experience in Deep Learning, Modelling/Performance Analysis, or Parallel Programming may be required.
- Knowledge or experience in Hardware Control Programming, GPU Acceleration, Parallel Processing (CUDA), High-Performance Computing (HPC), or Embedded Systems may be required.
- Depending on the internship role, prior experience or knowledge may be required in Verilog, SystemVerilog, VHDL, CUDA, Linux, C, C++, Python, Perl, modern graphics APIs (DirectX, OpenGL, Vulkan), GPU Computing (CUDA, OpenCL), revision control (Perforce, Git), or HPC (MPI, OpenMP).
- Work on projects during the 12-week full-time internship that have a measurable impact on NVIDIA’s business.
About the company
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
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Simplify's Take
What believers are saying
- AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
- Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
- Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.
What critics are saying
- Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
- Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
- Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.
What makes NVIDIA unique
- Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
- The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
- People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.
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Benefits
- Company Equity
- 401(k) Company Match