RAI AI Engineer, Reinforcement Learning

REVEL is an AI robotics company developing physical intelligence for general-purpose humanoid robots. We capture the force, dexterity and intent of human work with our Neural Gambit wearable, and use it to train RAI, the intelligence that powers our robots. REVEL is headquartered in Palo Alto, California, with R&D and engineering facilities in Prague and Hradec Králové, Czech Republic. This role is on-site with our engineering team in the Czech Republic.

Design RL and post-training methods to make policies robust and reliable. Our RAI team builds the core intelligence that powers REVEL robots, learning from the force and intent Neural Gambit captures.

Responsibilities

• Train and evaluate models on REVEL's human-demonstration data

• Build scalable, reproducible training and evaluation pipelines

• Collaborate across the RAI, hardware and data teams

• Push results from research into production on the robot

Requirements

• Track record of building and training RL policies (PPO, SAC, offline RL, or similar), with real depth on how they work, not just how to call them

• Applied RL to robotics or physical-system control, and taken policies beyond simulation to run and validate on real hardware.

• Comfortable working in a physics simulator (Isaac Lab, MuJoCo, or equivalent) to train and stress-test policies before they touch hardware

• A bias to ship and iterate quickly, in a small team where you'll own problems end to end

Bonus qualifications

• Locomotion or legged-robot RL experience

• Understanding of robot dynamics, control theory, or whole-body control

• Exposure to VLA or other foundation models applied to robotics

• Offline RL, imitation learning, or approaches that blend demonstration data with interaction

• Publications or strong open-source work in RL, ML, or robotic