Humanoid Locomotion Reinforcement Learning Engineer
Pubblicato il 16-09-2026 - Generative Bionics in Italia
Location: Via Melen 83, 16152 Genoa, Italy Contract: Full-time, Permanent About Us Generative Bionics is a deep-tech company building humanoid robot platforms to deploy human-centered Physical AI. We design intelligent, capable machines that work alongside people in real-world environments — developed in Genova, Italy. Role We are looking for a talented and driven Humanoid Locomotion & Reinforcement Learning Engineer to develop advanced locomotion and whole-body motion capabilities for our humanoid robot platform. In this role, you will work at the intersection of robotics, machine learning, and control systems, designing and deploying reinforcement learning-based solutions that enable robust, dynamic, and adaptive robot behavior. You will contribute to the full development pipeline, from simulation and policy training to sim-to-real transfer and deployment on physical robots. Responsibilities Develop and train reinforcement learning policies for humanoid locomotion, balance control, and whole-body motion; Design motion generation, imitation learning,
and motion retargeting pipelines using demonstrations, motion capture data, and reference trajectories; Build and maintain accurate robot, actuator, and contact models using simulation environments such as Isaac Lab, Isaac Sim, MuJoCo, or equivalent platforms; Develop domain randomization, system identification, and adaptation techniques to improve sim-to-real transfer performance; Deploy, validate, and optimize learned control policies on physical robots using Python and C++; Implement monitoring, fall detection, recovery strategies, and policy validation mechanisms to ensure safe robot operation; Analyze performance through simulation results, telemetry, robot logs, and experimental testing; Collaborate closely with Mechanical, Electronics, Perception, Controls, and AI teams to integrate locomotion capabilities into the humanoid platform; Requirements Master’s degree or PhD in Robotics, Control Engineering, Machine L