Role at a glance
- Salary
- $38 – $94/hr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Internship
- Experience
- Strong background in research with publications at top conferences.
- Education
- Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for...
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Role Summary
This Ph.D. engineering internship is part of NVIDIA’s Computer Architecture and Systems teams. Interns develop research and technology in GPU and CPU architectures, systems, operating systems, AI systems, and distributed systems, with results that can support new products and published research.
What You'll Do
- Design and implement novel ideas in GPU and CPU architectures, systems architectures, operating systems, AI systems, and distributed...
- Collaborate with team members, other teams, and external researchers.
- Transfer research to product groups to enable new products or types of products.
- Deliver prototypes, patents, products, and/or original research publications.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Active enrollment in a Ph.D. program in Computer Science, Electrical Engineering, or a related field for the full internship; anticipated graduation date must be indicated on a resume or CV. Strong research background with publications at top conferences, plus excellent communication and collaboration skills.
Required
- C
- C++
- Python
- CUDA
Preferred
- Chip-level and system-level architecture
- GPU and multi-GPU architecture
- Scalable memory systems and new memory technologies
- Scalable on-chip and off-chip interconnects
- Chip-level and system-level scheduling
- Power, performance, and energy-efficiency in large-scale systems
- Specialized accelerators for AI algorithms, crypto algorithms, and databases
- Hardware-software co-design
Original job description
Content provided by the employer
Original job description
Content provided by the employer
By submitting your resume, you acknowledge that your Ph.D. Engineering internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and you agree to our Terms of Service. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.
Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Computer Architecture and Systems teams. We’re seeking strategic, ambitious, hard-working, collaborative, and creative individuals who are passionate about helping us tackle challenges no one else can solve.
Learn more about Research at NVIDIA.
What you will be doing:
Design and implement novel ideas in GPU and CPU architectures, systems architectures, operating systems, AI systems, and distributed systems that advance computing, graphics, media processing, and related technologies central to NVIDIA's business.
Collaborate with other team members, teams, and/or external researchers.
Transfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.
What we need to see:
Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.
Depending on the internship, prior experience or knowledge requirements could include the following programming skills and technologies: C, C++, Python, CUDA
Strong background in research with publications at top conferences.
Excellent communication and collaboration skills.
Potential internships require research experience in at least one of the following areas:
Chip-level and System-level Architecture
GPU and Multi-GPU Architecture Scalable memory systems and new memory technologies
Scalable on-chip and off-chip interconnects
Chip-level and system-level scheduling
Power, performance, and energy-efficiency in large-scale systems
Specialized accelerators for workloads like AI algorithms, crypto algorithms, databases, etc.
Hardware-software co-design
Systems for AI/ML
Systems Infrastructure for large LLM training and inference
Systems/AI algorithms codesign (e.g., for sparsity) \
AI/ML for systems (hardware design, code optimization, etc.)
ML for EDA
Programming Systems
GPU-accelerated algorithms
Languages and programming models for parallel computing
Optimizing compilers and AI-based performance assistants
Distributed runtime systems
Systems software and operating system interfaces
Optimizing GPU-accelerated workloads
Compilers and code verification
High-Performance Networking and Interconnects
Large-scale GPU networking
Topologies, routing, and congestion control
Networking techniques at the intersection of scale-out and scale-up
VLSI and Electronic Design Automation (EDA)
GPU Accelerated EDA
Click here to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.You will also be eligible for Intern benefits.
Applications are accepted on an ongoing basis.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.