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.