NVIDIA 2026 Internships: Deep Learning - US

Position Overview

NVIDIA internships offer an excellent opportunity to expand your career and get hands-on experience with one of our industry-leading Deep Learning teams. We're seeking strategic, ambitious, hard-working, and creative individuals who are passionate about tackling challenges no one else can solve. Throughout the 12-week full-time internship, students will work on projects that have a measurable impact on our business.

Responsibilities

Potential Internships in this field include:

Deep Learning Applications & Algorithms

• Developing algorithms for deep learning, data analytics, or scientific computing to improving performance of GPU implementations
• Course or internship experience related to the following areas could be required: Deep Neural Networks, Linear Algebra, Numerical Methods and/or Computer Vision, Software Design, Computer Memory (Disk, Memory, Caches), CPU and GPU Architectures, Networking, Numeric Libraries, Embedded System Design and Development, Drivers, Real-Time Software

Deep Learning Frameworks & Libraries

• Building underlying frameworks and libraries to accelerate Deep Learning on GPUs
• Contributing directly to software packages such as JAX, PyTorch, and TensorFlow, integrating the latest library (e.g., cuDNN) or CUDA features, performance tuning, and analysis
• Optimizing core deep learning algorithms and libraries (e.g., CuDNN, CuBLAS), maintaining build, test, and distribution infrastructure for these libraries and deep learning frameworks on NVIDIA supported platforms
• Course or internship experience related to the following areas could be required: Computer Architecture (CPUs, GPUs, FPGAs or other accelerators), GPU Programming Models, Performance-Oriented Parallel Programming, Optimizing for High-Performance Computing (HPC), Algorithms, Numerical Methods

Requirements & Skills

• 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
• Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies: C, C++, CUDA, Python, x86, ARM CPU, GPU, Linux, Direct3D, Vulkan, OpenGL, OpenCL, Spark, Perl, Bash/Shell Scripting, Container Tools (Docker/Containers, Kubernetes), Infrastructure Platforms (AWS, Azure, GCP), Data Technologies (Kafka, ELK, Cassandra, Apache Spark), React, Go