Research Intern - Reinforcement Learning, Self-Driving

The Robot Age; Sunnyvale (CA); Hybrid; USD 34,000 - 55,000; Full time

Job summary

Applied Intuition’s research group invites you to join as an internship focused on reinforcement learning for autonomy. You will work on RL for large-scale autonomous systems, including self-play and neural-simulation based closed-loop RL, with potential to transfer to deployed programs.

You will collaborate with research scientists and engineers, use our data and infrastructure to connect experiments to real-world autonomy tasks, and contribute to publishable work while pursuing graduate

Qualifications

• 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.

Responsibilities

• 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.

Skills

Reinforcement learning

Autonomy systems

Independent & collaborative work

Education

Graduate study in ML/Robotics

Tools

Python

PyTorch

TensorFlow

Job description

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.

What you would work on

• 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.

What they are asking for

• 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.

Why this one is worth a look

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.