Robotics Learning Engineer (RL/IL)

Oversonic Robotics Srl; Milano; Hybrid; EUR 55,000 - 90,000; Full time

Benefits offered by this job

Hybrid work environment

Smart Working: 1 day/week

Job summary

Oversonic Robotics Srl is seeking a researcher to develop learning-based control strategies for humanoid robots. You will build training pipelines, design diverse task environments, and manage experiments from simulation to real-world validation.

The role requires strong Python and PyTorch skills, experience with RL algorithms, and a proven ability to translate learning into reliable robot behaviors while addressing sim-to-real challenges.

Qualifications

• MS/PhD in relevant field.
• 2+ years ML/RL/robotics experience.
• Strong Python + PyTorch coding.
• Familiar with PPO, SAC, RL robotics.

Responsibilities

• Design, implement and iterate RL/IL training pipelines for humanoid tasks in simulation and real world.
• Create diverse task suites for manipulation, navigation, whole-body coordination in simulation.
• Manage training experiments: Hyperparameter tuning, Benchmarking, Logging and Failure analysis.
• Collaborate with multidisciplinary teams including: Motion and control engineers, Mechanical design team, Simulation engineers.
• Support sim-to-real transfer by adapting policies to real robot constraints and validating performance during deployment.

Skills

Python

PyTorch

Reinforcement learning

Machine learning

RL algorithms

Robotics concepts

Education

MS or PhD in Robotics/Automation/CS

Tools

Isaac Lab

Stable Baselines

Job description

Responsible 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.

Responsibilities

• Design, implement and iterate RL/IL training pipelines for humanoid tasks in simulation and in the real world.
• Design and implement diverse task suites for manipulation, navigation, and whole-body coordination in simulation.
• Manage training experiments and evaluation loops: Hyperparameter tuning, Benchmarking, Logging and Failure analysis.
• Collaborate closely with multidisciplinary teams including: Motion and control engineers, Mechanical design team, Simulation engineers.
• Support sim-to-real transfer by adapting policies to real robot constraints and validating performance during deployment.

Requirements

• Ms or Phd in Robotics, Automation, Computer Science or related field.
• At least 2 years experience in ML / RL / robotics.
• Strong Python + PyTorch. You can profile, debug numerics, and write maintainable code.
• Familiarity with RL algorithms (PPO, SAC, etc.) and robotics (states, control, kinematics).
• Experience solving real problems using reinforcement learning policies in any domain.
• Strong ownership mindset with ability to document experiments and communicate trade-offs clearly.

Nice to have

• Experience with: Isaac Lab / RL Games / Stable Baselines
• Experience with sim-2-real challenges

Additional information

• Contract Type: Full-time
• Smart Working: Available (e.g., 1 day/week, subject to team policy)
• Driving Licence: Required

Why Join Oversonic Robotics?

• Contribute to a pioneering company shaping the future of humanoid robotics in Italy.
• Work with cutting-edge technology with real-world impact.
• Collaborate with a passionate and innovative team in a hybrid work environment.
• Join a company committed to sustainability, transparency, and social benefit.
• Enjoy opportunities for professional growth and influence our technological direction.