NVIDIA 2026 Internships: PhD Computer Architecture and Systems Research at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Technology, AI, SemiconductorIndustries

Requirements

Actively enrolled in a university pursuing a PhD degree in Computer Science, Electrical Engineering, or a related field, for the entire duration of the internship
Depending on the internship, prior experience or knowledge in programming skills and technologies: C, C++, Perl, Python, CUDA
Strong background in research with publications at top conferences
Excellent communication and collaboration skills
Research experience in at least one of the following areas: Hardware-software co-design, Computer Architecture, GPU and Multi-GPU Architecture, Scalable memory systems, System-level GPU scheduling, Power, performance, and energy-efficiency in large-scale systems, Programming Systems, Parallel Computing, Optimizing GPU-accelerated workloads, Distributed Computing, Compilers, High-Performance Networking and Interconnects, Large-scale GPU networking, Topologies, routing, and congestion control, Circuits and microarchitecture for network controllers and switches, VLSI and Electronic Design Automation (EDA), GPU Accelerated EDA, Systems for AI/ML, Systems Infrastructure for large LLM training and inference, ML for hardware systems (ML for EDA)

Responsibilities

Design and implement algorithms, hardware, and software solutions that advance computing, graphics, media processing, and related technologies central to NVIDIA's innovation
Collaborate with other team members, teams, and/or external researchers
Transfer research to product groups to enable new products or types of products
Deliver results including prototypes, patents, products, and/or publishing original research

Skills

Key technologies and capabilities for this role

CC++PerlPythonCUDAComputer ArchitectureComputer SystemsResearchAlgorithmsHardware Design

Questions & Answers

Common questions about this position

What are the eligibility requirements for this internship?

You must be actively enrolled in a university pursuing a PhD degree in Computer Science, Electrical Engineering, or a related field for the entire duration of the internship.

What programming skills are needed for these internships?

Depending on the internship, prior experience or knowledge in C, C++, Perl, Python, and CUDA is required.

What research experience is required?

Candidates need a strong background in research with publications at top conferences, and experience in at least one area such as hardware-software co-design, computer architecture, GPU architecture, scalable memory systems, or related fields.

How is compensation structured for these internships?

Our internship hourly rates are a standard pay based on the position and your location.

What qualities make a strong candidate for these internships?

NVIDIA seeks strategic, ambitious, hard-working, and creative individuals who are passionate about tackling challenges, with excellent communication and collaboration skills.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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