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NVIDIA · 3 days ago

NVIDIA 2026 Internships: Deep Learning Computer Architecture - US

United States

Full-time

Remote

New Grad

NVIDIA is a pioneer in accelerated computing, transforming industries through AI and digital twins. They are offering internships in Deep Learning Computer Architecture, where students will work on impactful projects and gain hands-on experience in the field.

Artificial Intelligence (AI)Consumer ElectronicsGPUHardwareSoftwareVirtual Reality

Growth Opportunities

Responsibilities

By submitting your resume, you’re expressing interest in one of our 2026 Deep Learning Computer Architecture Internships

We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities

Throughout the 12-week minimum full-time internship, students will work on projects that have a measurable impact on our business

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

Qualification

GPU ArchitectureDeep LearningGPU ComputingParallel ProgrammingC++PythonCUDATensorFlowPyTorchPerformance AnalysisNeural Network ArchitecturesCompiler Programming

Required

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

Course or internship experience related to Computer Architecture experience in one or more of these focus areas: GPU Architecture, CPU Architecture, Deep Learning, GPU Computing, Parallel Programming, or High-Performance Computing Systems

GPU Computing (CUDA, OpenCL, OpenACC), GPU Memory Systems, Deep Learning Frameworks (PyTorch, TensorFlow, Keras, Caffe), HPC (MPI, OpenMP)

Modelling/Performance Analysis, Parallel Processing, Neural Network Architectures, GPU Acceleration, Deep Learning Neural Networks, Compiler Programming

Performance Modeling, Profiling, Optimizing, and/or Analysis

Prior experience or knowledge requirements could include the following programming skills and technologies: C, C++, Python, Perl, GPU Computing (CUDA, OpenCL, OpenACC), Deep Learning Frameworks (PyTorch, TensorFlow, Caffe), HPC (MPI, OpenMP)