PhD Research Intern, Architecture – 2027
$0k - $0k • Remote • US, CA, Santa Clara
Posted 7d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
NVIDIA's Architecture Research Group is seeking a PhD intern to contribute to defining the future of GPU and data-center computing. This role involves exploring foundational research questions in areas such as GPU microarchitecture, memory systems, large-scale data-center hardware, and emerging accelerators, with a focus on the architectural implications of AI and scientific computing workloads. The intern will apply knowledge of computer architecture, parallel computing, compilers, and runtime systems to identify and develop new hardware and hardware-software co-design opportunities, working alongside researchers and product architects to formulate research questions, evaluate concepts, and build necessary models and simulators.
Responsibilities
- Investigate new architecture concepts for future GPUs, memory systems, accelerators, and data-center-scale computing platforms.
- Study emerging workloads to identify architectural bottlenecks and opportunities.
- 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.
- Communicate research findings through presentations, technical reports, and potentially publications.
- Help transfer successful research ideas, methodologies, and tools into NVIDIA product teams.
Requirements
- Pursuing a PhD Degree in a relevant discipline (CS, CE, EE, Physics, Math).
- Relevant industrial and university experience in hardware, software, or algorithm development.
- 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.
Benefits
- Internship hourly rates based on position, location, year in school, degree, and experience.
- Eligibility for Intern benefits.