pResponsible for developing and deploying learning-based control strategies for humanoid robot models, with a focus on reinforcement and imitation learning. The role centers on building robust training pipelines, designing diverse task environments, and managing experimentation workflows from simulation to real-world validation. It involves translating learning algorithms into reliable robot behaviors, addressing sim-to-real challenges, and ensuring performance through systematic benchmarking and analysis. Close collaboration with control, simulation, and hardware teams is required to align learned policies with physical system constraints and operational goals. /ppResponsibilities /pulliDesign, implement and iterate RL / IL training pipelines for humanoid tasks in simulation and in the real world. /liliDesign and implement diverse task suites for manipulation, navigation, and whole-body coordination in simulation. /liliManage training experiments and evaluation loops : Hyperparameter tuning, Benchmarking, Logging and Failure analysis. /liliCollaborate closely with multidisciplinary teams including:



Motion and control engineers, Mechanical design team, Simulation engineers. /liliSupport sim-to-real transfer by adapting policies to real robot constraints and validating performance during deployment. /li /ulpRequirements /pulliMs or Phd in Robotics, Automation, Computer Science or related field. /liliAt least 2 years experience in ML / RL / robotics. /liliStrong Python + PyTorch. You can profile, debug numerics, and write maintainable code. /liliFamiliarity with RL algorithms (PPO, SAC, etc.) and robotics (states, control, kinematics). /liliExperience solving real problems using reinforcement learning policies in any domain. /liliStrong ownership mindset with ability to document experiments and communicate trade-offs clearly. /li /ulpNice to Have /pulliExperience with: /liliExposure to: /liliExperience with sim-2-real challenges /li /ulpRobotics Learning Engineer (RL / IL) • Lombardy, Italy /p #J-18808-Ljbffr

📌 Robotics Learning Engineer (Rl / Il) (Bardi)
🏢 Oversonic
📍 Bardi