PhD Research Intern, Architecture – 2027
NVIDIAJob Title
PhD Research Intern, Architecture – 2027
Role Summary
The NVIDIA Architecture Research Group seeks a PhD intern to research GPU and data-center architectures, memory systems, and hardware–software co-design. The intern will develop and evaluate architecture concepts by building models, simulators, prototypes, and experimental infrastructure and will collaborate with researchers and product architects to test and transfer promising ideas into products.
Intern hourly rate: 38–94 USD.
Experience Level
Entry-level internship for PhD students; no specific years of post-degree experience required.
Responsibilities
Key responsibilities include:
- Investigate architecture concepts for GPUs, accelerators, memory systems, and data-center platforms.
- Analyze emerging workloads to identify architectural bottlenecks and opportunities.
- Explore hardware–software co-design across architecture, compilers, runtimes, programming models, and applications.
- Develop models, simulators, prototypes, and experimental tools to evaluate ideas.
- Research memory hierarchy, coherence, consistency, data movement, and system-level programmability.
- Collaborate with researchers, GPU architects, software teams, and product groups to develop and evaluate concepts.
- Communicate research findings through presentations, technical reports, and publications.
- Help transfer successful research ideas, methodologies, and tools into product teams.
Requirements
Must-have technical skills and experience:
- Relevant industrial or university experience in hardware, software, or algorithm development.
- Strong programming ability in C/C++ and experience with scripting languages.
- Experience with CUDA and GPU programming.
- Experience building computer system simulators.
- Experience developing efficient low-level software tools (runtime systems, binary translators, compilers).
- Strong background in computer architecture and parallel computer architectures.
Nice-to-have:
- Prior research publications at ISCA, MICRO, ASPLOS, HPCA, MLSys, or similar venues.
- Experience with GPU profiling tools and running deep-learning models on GPUs.
- Familiarity with generative AI coding tools.
Education Requirements
Pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Physics, Mathematics, or a related technical discipline.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
