Research Intern - Reinforcement Learning, Self-Driving

What the role actually is

This internship sits in Applied Intuition's research group and focuses on reinforcement learning for autonomy. The work includes closed-loop RL, self-play, VLA post-training, neural simulation, and methods that can transfer across self-driving and robotic systems.

• Run research on reinforcement-learning topics for large-scale autonomy systems.
• Explore self-play RL, neural-simulation-based closed-loop RL, reward learning, and behavior learning.
• Collaborate with research scientists and engineers on publishable work.
• Use Applied's data and infrastructure to connect research experiments to deployed autonomy programs.

• Current graduate study in machine learning, computer vision, graphics, robotics, or a related field.
• A strong research background in reinforcement learning or adjacent autonomy topics.
• Ability to work independently and collaboratively on research projects.
• Interest in scalable autonomy and robotic systems.

Applied's research group works across autonomous vehicles, trucks, mining and construction machines, humanoids, and dexterous hands. That makes this a useful internship to watch if you care about RL methods that move beyond isolated demos into physical AI programs.