NVIDIA 2027 Summer Internships: Ph.D. Engineering
NVIDIAJob Title
NVIDIA 2027 Summer Internships: Ph.D. Engineering
Role Summary
Ph.D. engineering interns perform research and prototype systems in GPU/CPU architecture, systems, compilers, AI systems, and related areas within NVIDIA's Computer Architecture and Systems teams.
Interns collaborate with researchers and product groups to convert research into prototypes, publications, patents, or product-ready technology.
Experience Level
Entry-level internship for Ph.D. students actively enrolled in a doctoral program; this is a student internship position rather than a professional-level hire.
Responsibilities
Primary responsibilities include research, prototyping, and collaboration to advance computing and systems technologies:
- Design and implement novel ideas in GPU/CPU architectures, systems architecture, operating systems, AI systems, and distributed systems.
- Prototype research results and evaluate performance, scalability, and correctness.
- Collaborate with team members, cross-functional teams, and external researchers.
- Transfer research outcomes to product groups; deliverables may include prototypes, patents, products, and peer-reviewed publications.
Requirements
Must-have technical skills and experience for successful candidates:
- Strong research record with publications at top conferences.
- Proficiency in programming languages commonly used in systems and research projects, e.g. C, C++, and Python.
- Familiarity with GPU programming and CUDA where relevant to the internship.
- Excellent written and verbal communication and collaboration skills.
- Ability to produce reproducible prototype implementations and document results.
Nice-to-have areas of experience (depending on the specific internship):
- Chip- and system-level architecture, scalable memory and interconnects, and hardware-software co-design.
- Systems for AI/ML, including infrastructure for large-model training and inference.
- Programming systems, optimizing compilers, and distributed runtime systems.
- High-performance networking and interconnects for large-scale GPU deployments.
- VLSI and EDA, including GPU-accelerated EDA workflows.
Education Requirements
Must be actively enrolled in a Ph.D. program in Computer Science, Electrical Engineering, or a related technical field for the full duration of the internship. Anticipated graduation date (month and year) must be clearly indicated on the resume or CV.
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.
