NVIDIA 2026 Internships: PhD Generative AI Research at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

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
Programming skills in Python, C++, CUDA, and Deep Learning Frameworks (PyTorch, JAX, Tensorflow, etc.)
Strong background in research with publications at top conferences
Excellent communication and collaboration skills
Research experience in at least one of the following areas: Multimodal Foundation Models, Diffusion Models, World Models, Image/Video/Audio Generation, Large Language Models, Vision-Language Models, Action-Based Transformers, Long Context Methods, Physics-Based Simulation, Flow Based Generative Models, Synthetic Data Generation, AI for Science, Protein/Molecule Generation, Climate Modeling and Weather Forecasting, Partial Differential Equations (PDEs)
Experience with large-scale model training (preferred)

Responsibilities

Design and implement algorithms that push the boundaries of generative AI, computer vision, robotics, and other technology domains relevant to NVIDIA’s business
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

PythonC++CUDAPyTorchJAXTensorFlowDeep LearningComputer VisionRoboticsGenerative AI

Questions & Answers

Common questions about this position

What is the hourly rate for the NVIDIA 2026 Generative AI Research Internships?

The hourly rate for interns ranges from 30 USD to 94 USD, based on the position, location, year in school, degree, and experience.

Are interns eligible for benefits at NVIDIA?

Yes, interns are eligible for intern benefits.

What are the required skills and experience for these internships?

Candidates must be enrolled in a PhD program in Computer Science, Electrical Engineering, or related field, with skills in Python, C++, CUDA, Deep Learning Frameworks like PyTorch, JAX, Tensorflow; a strong research background with publications at top conferences; and excellent communication and collaboration skills.

What research areas are relevant for these NVIDIA internships?

Internships require research experience in at least one area such as Multimodal Foundation Models, Diffusion Models, World Models, Image/Video/Audio Generation, Large Language Models, Vision-Language Models, and others including AI for Science and Climate Modeling.

What makes a strong candidate for NVIDIA's Generative AI Research Internships?

Strong candidates are strategic, ambitious, hard-working, creative PhD students passionate about generative AI, with relevant research experience, publications, and technical skills in programming and deep learning frameworks.

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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