Research Engineer - Reinforcement Learning, Self-Driving

What the role actually is

Applied Intuition is hiring research engineers for its AI research group. This opening focuses on reinforcement learning for self-driving systems, with the broader team working across end-to-end autonomy and robotic generalist research.

The role is research engineering rather than product design, but it fits the board's autonomy-research lane because evaluation, simulation, and behavior quality are central to whether autonomy becomes usable in the world.

What you would work on

• Implement reinforcement-learning methods for autonomous driving research
• Build experiments and tooling that help compare behavior policies
• Work with researchers on physical AI systems spanning simulation and real-world autonomy
• Translate research ideas into reliable code and repeatable evaluation loops

What they are asking for

• Strong engineering background in ML, reinforcement learning, robotics, or autonomy
• Ability to implement research methods and debug complex model behavior
• Experience with experimentation, evaluation, and production-aware research workflows
• Interest in self-driving systems and physical AI infrastructure

Why this one is worth a look

The interesting piece here is the infrastructure context. Reinforcement learning for autonomy only matters if teams can measure, compare, and trust behavior changes; Applied's business gives that research a direct path into autonomy tooling.