NVIDIA 2026 Internships: PhD Autonomous Vehicles Research at NVIDIA

Santa Clara, California, United States

NVIDIA Logo
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

Python
C++
CUDA
PyTorch
TensorFlow
Deep Learning

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.

Land your dream remote job 3x faster with AI