Summer 2026
NVIDIA 2026 Internships: PhD Computer Vision and Deep Learning Research
US
Posted on 2/21/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$30 - $94/hr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
 AI & Machine Learning (1) |
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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.
- Prior experience or knowledge 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.
- Potential internships require research experience in at least one of the following areas: 3D Vision and Scene Understanding, Optical Flow/Scene Flow, SLAM, Depth Estimation, Digital Twins, Human-Centric Vision, Human Motion Modeling, Human avatar creation (Gaussian Avatar, Neural Human Avatars, Text to Avatar Generation), Physics-Based Clothing/Hair/Body Simulation, Neural Rendering and Generative 3D, Diffusion Models, World Models, Neural Radiance Fields (NeRFs), Novel View Synthesis, 3D Content Creation, Model Architectures and Efficiency, Efficient Deep Learning, Model pruning and compression, Efficient vision transformers, Neural Architecture Search (NAS), Multimodal and Vision-Language Models, Synthetic data generation, Weather and Atmospheric Simulation.
- 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.
- Experience with large-scale model training is a plus.
- Potential internships require research experience in at least one of the following areas: 3D Vision and Scene Understanding; Optical Flow/Scene Flow; SLAM; Depth Estimation; Digital Twins; Human-Centric Vision; Human Motion Modeling; Human avatar creation (Gaussian Avatar, Neural Human Avatars, Text to Avatar Generation); Physics-Based Clothing/Hair/Body Simulation; Neural Rendering and Generative 3D; Diffusion Models; World Models; Neural Radiance Fields (NeRFs); Novel View Synthesis; 3D Content Creation; Model Architectures and Efficiency; Efficient Deep Learning; Model pruning and compression; Efficient vision transformers; Neural Architecture Search (NAS); Multimodal and Vision-Language Models; Synthetic data generation; Weather and Atmospheric Simulation.
NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
Simplify's Take
What believers are saying
- May 2026 Q1 revenue reached $81.6 billion, driven by 92% data-center growth.
- Nvidia secured $30 billion cloud agreements and $80 billion buyback authorization.
- CPU, optical networking, and physical-AI initiatives open adjacent markets beyond GPUs.
What critics are saying
- AMD and Intel are targeting Nvidia's $200 billion CPU opportunity aggressively.
- TSMC dependency makes Blackwell and Vera Rubin shipments vulnerable to Taiwan disruption.
- Investors are pricing post-2027 slowdown, compressing valuation on any execution miss.
What makes NVIDIA unique
- Nvidia dominates AI training GPUs with over 80% market share in 2025.
- Blackwell and Vera Rubin create a full-stack AI infrastructure platform, not chips alone.
- CUDA, networking, and system partnerships lock customers into Nvidia's software and hardware ecosystem.
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