February 6, 2025
Intern • On-site
$30 - $90/hr
Santa Clara, CA
As a PhD Intern on the Predictions, Planning, and Controls team within NVIDIA’s Autonomous Vehicles group, you will play an active role in producing safe and comfortable trajectories that can be executed by the vehicle. This is done using machine learning, optimization, and optimal control.
The goal of this internship is to improve a neural network used to generate trajectories for the vehicle. This will involve performing experiments with different network architectures, designing new loss functions, augmenting the training data with synthetic perturbations, running and validating the network in simulation, and ultimately testing the network on board the vehicle. You will work with other engineers to train the network, as well as validate the network’s performance on a large data set. This includes collaborating with a diverse group of engineers across machine learning, infrastructure, and computational performance teams to make a meaningful contribution in enabling autonomous driving around the world.
Pursuing a PhD degree in Computer Science, Mathematics, Electrical Engineering or related field
Experience with Pytorch
Excellent Python programming skills
Experience training neural networks
Understanding of modern neural network architectures: Convolution, ResNet, Transformers
Background with Reinforcement Learning or Optimal Control would be helpful but not required
Experience with C++
Previous internship or academic research experience is a plus, including experience working in Robotics and Autonomous Vehicles.
You will also be eligible for Intern benefits. NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.