By submitting your resume, you’re expressing interest in one of our 2026 Computer Vision and Deep Learning focused Research 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.

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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.

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Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Computer Vision 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.

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What you will be doing:

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• Design and implement novel computer vision and deep learning methods.

• Collaborate with other team members, teams, and/or external researchers.

• Transfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.

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What we need to see:

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• Must be 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.    

• Depending on the internship, prior experience or knowledge requirements could include the following programming skills and technologies: Python, C++, CUDA, Deep Learning Frameworks (PyTorch, TensorFlow, etc.)

• Strong background in research with publications at top conferences.

• Excellent communication and collaboration skills.

• Experience with large-scale model training is a plus.

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Potential internships require research experience in at least one of the following areas:

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3D Vision and Scene Understanding

• Optical Flow/Scene Flow

• SLAM

• Depth Estimation

• Digital Twins

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Human-Centric Vision

• Human Motion Modeling

• Human avatar creation (Gaussian Avatar, Neural Human Avatars, Text to Avatar Generation)

• Physics-Based Clothing/Hair/Body Simulation

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Neural Rendering and Generative 3D

• Diffusion Models

• World Models

• Neural Radiance Fields (NeRFs)

• Novel View Synthesis

• 3D Content Creation

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Model Architectures and Efficiency

• Efficient Deep Learning

• Model pruning and compression

• Efficient vision transformers

• Neural Architecture Search (NAS)

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