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Policy Design & Training: You design and train the learning-based policies that map multimodal sensing, from vision and language down to raw tactile and IMU data, into smooth, precise, and safe hardware actions.
Multi-Contact Manipulation: You sit at the intersection of imitation learning, reinforcement learning, and physical deployment. Your problem is the hard one: multi-contact manipulation on real, underactuated, tactile-rich hardware.
Dexterous Hand Control: You teach NEURA's hands to manipulate the world with human-like dexterity
Collaboration & Execution: You work closely with ML, robotics, and software teams to deliver trained policies that work on the hands.
Master's or PhD in Robotics, Computer Science, Machine Learning, or a related field with a strong focus on robotic manipulation or reinforcement learning
Hands-on experience training manipulation policies with imitation learning or deep RL on physical robot arms or dexterous hands
Deep familiarity with GPU-accelerated simulation (Isaac Lab and Isaac Sim, or MuJoCo), including building custom environments and assets
Strong PyTorch, with experience using robot-learning libraries such as Stable-Baselines3, Ray RLlib, or LeRobot
Solid foundations in kinematics, dynamics, spatial transforms, and closed-loop control
Proficient Python and C++, clean reproducible code, Git, and Docker
Nice to have:
Experience with teleoperation hardware such as VR controllers, data gloves, or vision-based hand tracking
Experience training or fine-tuning VLA or diffusion-based architectures
Experience with tendon-driven or highly underactuated mechanical systems
Skills Required
- Master's or PhD in Robotics, Computer Science, Machine Learning, or related field with strong focus on robotic manipulation or reinforcement learning
- Hands-on experience training manipulation policies with imitation learning or deep RL on physical robot arms or dexterous hands
- Deep familiarity with GPU-accelerated simulation (Isaac Lab, Isaac Sim, or MuJoCo), including building custom environments and assets
- Strong PyTorch experience and familiarity with robot-learning libraries such as Stable-Baselines3, Ray RLlib, or LeRobot
- Solid foundations in kinematics, dynamics, spatial transforms, and closed-loop control
- Proficient Python and C++, clean reproducible code, Git, and Docker
- Experience with teleoperation hardware such as VR controllers, data gloves, or vision-based hand tracking
- Experience training or fine-tuning VLA or diffusion-based architectures
- Experience with tendon-driven or highly underactuated mechanical systems
What We Do
NEURA Robotics is a German high-tech company founded in 2019 in Metzingen near Stuttgart with the vision to revolutionize the world of robotics. More than 180 team members from over 30 countries are working on advanced technologies in the fields of environmental perception, drive and control technology, material science, mechanical design, and artificial intelligence. We are expanding the cognitive capabilities of robots and make breakthrough advances in a variety of areas to bring robots and humans closer together, making many areas of work more attractive, creative, and social again. That's why everything we do runs under the guiding principle "we serve humanity". In a very short period of time, NEURA Robotics has developed robots and technologies that are characterized above all by their outstanding performance as well as safe and human-centred way of working. In this way, a wide variety of application fields can be covered, from intelligent production to medical technology. All major robot components are developed and designed in-house. Imprint: https://www.neura-robotics.com/legal Privacy: https://www.neura-robotics.com/privacy
