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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
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NVIDIA 2027 Internships: Autonomous Vehicles and Robotics interns join the Autonomous Vehicles and Robotics team to work on projects with measurable business impact over a twelve-week period. In the autonomous vehicles domain, interns develop and train state-of-the-art deep neural networks for path generation while collecting training datasets and performing in-vehicle tests using simulators. Within robotics, the role involves building fundamental infrastructure and software platforms that power various robot applications. Candidates should possess expertise in computer vision, mapping, localization, SLAM, image processing, segmentation, operating systems, data structures, physics simulation, and cloud technologies. Required technical skills include C, C++17, CUDA, ROS, Python, OpenGL, Linux, sensor input devices like LiDAR and radar, and training frameworks such as TensorFlow, Keras, or PyTorch to solve complex challenges in autonomous navigation and robotic system architecture.
Develop and train state-of-the-art Deep Neural Networks for path generation.
Collect training datasets and measure real-time inference run-times using simulators and gyms.
Perform in-vehicle testing to validate autonomous vehicle systems.
Build fundamental infrastructure and software platforms for the Isaac platform.
Develop core software components that power robot applications and systems.
Implement computer vision, mapping, localization, and SLAM algorithms.
Develop validation frameworks for deep learning models.
Utilize CUDA, ROS, and Python to develop high-performance robotics software.
What we're looking for
Must be actively enrolled in a university pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field.
Resume must clearly indicate the anticipated graduation date (month and year).
Experience or knowledge in Computer Vision, Mapping, Localization, SLAM, Image Processing, or Segmentation may be required.
Experience or knowledge in Robotics, Autonomous Vehicles, Validation Frameworks for Deep Learning, Operating Systems, Data Structures, Physics Simulation, Simulators, Computer Graphics, Version Control, Cloud Technologies, or Linux may be required.
Proficiency in programming languages and technologies such as C, C++, C++17, CUDA, ROS, Python, OpenGL, and Training Frameworks (TensorFlow, Keras, PyTorch) may be required.
Experience with Sensor Input Devices including LiDAR, cameras, and radars may be required.
Python
C++
CUDA
PyTorch
TensorFlow
Deep Learning
Large-scale Model Training
LLMs
Multimodal Models
Sensor Fusion
Digital Twins
Simulation
Model Distillation
Inference Optimization
Control Barrier Functions
Deep Learning
CUDA
PyTorch
TensorFlow
JAX
cuDNN
cuBLAS
C++
C
Python
GPU Programming
High-Performance Computing
Linux
Docker
Kubernetes
Spark
Kafka
Cassandra
OpenCL
Vulkan
OpenGL
Direct3D
Bash
Go
Computer Vision
Deep Learning
Python
C++
CUDA
PyTorch
TensorFlow
3D Vision
Scene Understanding
Neural Rendering
Diffusion Models
NeRFs
Vision Transformers
Neural Architecture Search
Synthetic Data Generation
Python
C++
CUDA
PyTorch
JAX
TensorFlow
Deep Learning
Generative AI
Computer Vision
Large Language Models
Diffusion Models
Multimodal Foundation Models
World Models
Action-Based Transformers
Physics-Based Simulation
Synthetic Data Generation
Partial Differential Equations
Python
C++
CUDA
PyTorch
JAX
TensorFlow
MuJoCo
Deep Learning
Robotic Manipulation
Motion Planning
Reinforcement Learning
Sim-to-Real
Foundation Models
Robot Kinematics
Dynamics
Synthetic Data Generation