NVIDIA 2026 Internships: Deep Learning Computer Architecture 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 Bachelor's, Master's, or PhD degree in Electrical Engineering, Computer Engineering, or a related field, for the entire duration of the internship
Course or internship experience related to Computer Architecture in one or more of: GPU Architecture, CPU Architecture, Deep Learning, GPU Computing, Parallel Programming, or High-Performance Computing Systems
Experience with GPU Computing (CUDA, OpenCL, OpenACC), GPU Memory Systems, Deep Learning Frameworks (PyTorch, TensorFlow, Keras, Caffe), HPC (MPI, OpenMP)
Experience in Modelling/Performance Analysis, Parallel Processing, Neural Network Architectures, GPU Acceleration, Deep Learning Neural Networks, Compiler Programming
Experience in Performance Modeling, Profiling, Optimizing, and/or Analysis
Prior experience or knowledge of programming skills and technologies including C, C++, Python, Perl, GPU Computing (CUDA, OpenCL, OpenACC), Deep Learning Frameworks (PyTorch, TensorFlow, Caffe), HPC (MPI, OpenMP), depending on the role

Responsibilities

Work on projects that have a measurable impact on NVIDIA's business during the 12-week full-time internship
Collaborate with Deep Learning Computer Architecture teams to gain hands-on experience

Skills

Key technologies and capabilities for this role

GPU ArchitectureCPU ArchitectureDeep LearningGPU ComputingParallel ProgrammingHigh-Performance ComputingCUDAOpenCLOpenACCGPU Memory SystemsPyTorchTensorFlowKerasCaffeMPIOpenMPNeural Network Architectures

Questions & Answers

Common questions about this position

What is the hourly rate for the NVIDIA 2026 internships?

The hourly rate for interns ranges from 20 USD to 71 USD, based on the position, location, year in school, degree, and experience.

What benefits are offered to interns?

Interns are eligible for intern benefits, though specific details are not listed in the job description.

What education is required for these internships?

Candidates must be actively enrolled in a university pursuing a Bachelor's, Master's, or PhD degree in Electrical Engineering, Computer Engineering, or a related field for the entire duration of the internship.

What technical skills and experience are needed for the Deep Learning Computer Architecture internships?

Required experience includes Computer Architecture in areas like GPU/CPU Architecture, Deep Learning, GPU Computing, and Parallel Programming. Key technologies include C, C++, Python, CUDA, OpenCL, Deep Learning Frameworks (PyTorch, TensorFlow), and HPC tools (MPI, OpenMP). Skills in performance modeling, profiling, optimizing, and analysis are also important.

How can I increase my chances of being selected for an NVIDIA internship?

Highlight your enrollment in a relevant degree program in Electrical Engineering, Computer Engineering, or related fields, along with course or internship experience in GPU/CPU architecture, deep learning, CUDA, PyTorch/TensorFlow, and performance analysis. Demonstrate that you are strategic, ambitious, hard-working, creative, and passionate about solving complex challenges in accelerated computing.

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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