AI Manipulation Engineer (human)
Neura Robotics · Munich
- Company
- Neura Robotics
- Work style
- Onsite
- Employment
- Full Time
- Location
- Munich
- Published
- 2026-06-17
- Source checked
- 2026-10-24
- Listing source
- Ashby Job Postings API
About this role
YOUR MISSION & CHALLENGES - 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. WHAT WE CAN LOOK FORWARD TO - 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
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