NVIDIA 2026 Internships: PhD Autonomous Vehicles Research at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Autonomous Vehicles, AIIndustries

Requirements

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
Programming skills in Python, C++, CUDA, Deep Learning Frameworks (PyTorch, TensorFlow, etc.)
Strong background in research with publications at top conferences
Excellent communication and collaboration skills
Research experience in at least one of the following areas: Next-Generation AV Architectures, Chain-of-Thought Reasoning, Mixture-of-Experts, Diffusion-LLMs, Diffusion-based Trajectory Decoding, Novel Policy Training Strategies, Closed-loop Training, Off-policy RL, Online RL, Enforcing Consistency, Foundation and Multimodal Models, Vision-language models, Multimodal reasoning, Spatial Multimodal Models, Modality Alignment, Model Scaling, Synthetic data, Inference Efficiency, Inference Optimizations (e.g., parallel decoding, speculative decoding), Token Representations, Model Distillation, Simulation and Behavior Modeling, Digital Twins, Scenario Generation, World Models, Behavior/Traffic Modeling, End-to-End AV Systems, Mapless driving, World Representations, Beyond imitation learning, Safety-aware end-to-end models, Perception and Representation Learning, Multi-modal sensor fusion, 2D/3D detection, segmentation, depth estimation, scene understanding, neural representations, Safe and Trustworthy Autonomous Systems, Principled robustness, Model explainability, Control Barrier Functions (CBFs), Verification and Validation of Safety-Critical AI Systems, Trustworthy AI/ML for autonomy and robotics, Data-Strategies for AI, Benchmarking AV
Experience with large-scale model training (plus)

Responsibilities

Design and implement cutting-edge techniques in the field of vehicle autonomy
Collaborate with other team members, teams, and/or external researchers
Transfer research to product groups to enable new products or types of products
Deliver results including prototypes, patents, products, and/or publishing original research

Skills

Key technologies and capabilities for this role

PythonC++CUDAPyTorchTensorFlowDeep Learning

Questions & Answers

Common questions about this position

What are the key qualifications required for this NVIDIA PhD internship?

Candidates must be actively enrolled in a PhD program in Computer Science, Electrical Engineering, or a related field for the entire internship duration, with a strong background in research including publications at top conferences, and skills in Python, C++, CUDA, and Deep Learning Frameworks like PyTorch or TensorFlow.

What specific research areas are covered in these NVIDIA Autonomous Vehicles internships?

Internships focus on areas such as Next-Generation AV Architectures, Chain-of-Thought Reasoning, Mixture-of-Experts, Diffusion-LLMs, Off-policy RL, Foundation and Multimodal Models, Simulation and Behavior Modeling, End-to-End AV Systems, Perception and Representation Learning, and Safe and Trustworthy Autonomous Systems.

Is this a full-time or part-time internship, and what is the duration?

This information is not specified in the job description.

What compensation or benefits are offered for this internship?

This information is not specified in the job description.

What qualities make a strong candidate for these NVIDIA internships?

Strong candidates are strategic, ambitious, hard-working, creative individuals passionate about solving challenges in autonomous vehicles, with excellent communication and collaboration skills, plus experience in large-scale model training.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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