NVIDIA 2025 Internships: Artificial Intelligence and Deep Learning

By submitting your resume, you’re expressing interest in one of our 2025 Artificial Intelligence or Deep Learning 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. 

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.   

Our internships offer an excellent opportunity to expand your career and get hands on with one of our industry leading Artificial Intelligence and Deep Learning teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve. 

Throughout the minimum 12-week internship, students will work on projects that have a measurable impact on our business. We’re looking for students pursuing Bachelor's, Master's, or PhD degree within a relevant or related field. 

Potential Internships in this field include:  

Autonomous Vehicles 

• Developing and training state-of-the-art Deep Neural Networks for path generation 

• Collecting training datasets and real-time inference run-times using simulators/gyms as well as performing in-vehicle tests 

• Course or internship experience related to the following areas could be required: Computer Vision, Mapping, Localization, SLAM, Image Processing, Segmentation 

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 

Robotics 

• Building the fundamental infrastructure and software platforms of our system, working at the very heart of the software system, which will power every robot and application built with Isaac 

• Course or internship experience related to the following areas could be required: Robotics, Autonomous Vehicles, Validation Frameworks for Machine Learning/Deep Learning, Operating Systems and Data Structures (threads, processes, memory, synchronization), Physics Simulation, Simulators, Computer Graphics, Version Control, Computer Vision, Cloud Technologies 

Machine Learning 

• Developing and maintaining the first-generation MLaaS (Machine Learning as a Service) Platform including data ingestion, data indexing, data labeling, visualization, dashboards, and data viewers 

• Course or internship experience related to the following areas could be required: Machine Learning, Deep Learning, Accelerated Computing, GPU Computing, Deep Learning Frameworks, NVIDIA RAPIDS 

What we need to see:  

• Currently pursuing a Bachelor's, Master's, or PhD degree within Electrical Engineering, Computer Engineering, Computer Science, Artificial Intelligence or a related field 

• 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 

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