Your mission

We’re building something that doesn’t exist yet. Our startup, backed by teams in London and Milan, is working at the frontier of soft robotics. We’re looking for a Senior Robotics Research Engineer who lives at the intersection of machine learning, control theory, and software, and who wants to teach strange, compliant machines to move, and grasp exactly the way we intend.

Our lab is 20 minutes from Rondo Rataje, Poznań.

www.morph.inc

You’ll own the simulation, learning, and control stack that every one of our robots runs on. That means building simulators for systems that are hard to model, training policies that survive contact with the real world, and combining learned and model-based control where each works best. You’ll take soft bodies from first sim to robust real-world behaviour, and build the tools the rest of the team relies on to run experiments. Occasional travel to London and Milan comes with the role.

Your profile

• Have 5+ years of professional robotics software experience, or 3+ years after a PhD in Robotics, Machine Learning for Robotics, Controls, or a related field
• Have trained and deployed learned policies (reinforcement learning or imitation learning) on physical robots, not just in simulation
• Have taken a policy from simulation to hardware, and can tell us exactly where the reality gap bit you
• Are fluent in PyTorch or JAX, and comfortable running large-scale training in GPU-parallel simulators (Isaac Lab, MuJoCo/MJX, Brax, or similar)
• Know your control theory: state-space methods, LQR or MPC, state estimation, and when a classical controller beats a learned one
• Write strong modern C++ and clean Python that other engineers can build on
• Have used ROS 2 on real projects, not just tutorials
• Care about testing, code review, and reproducible experiments, because your code is the foundation others stand on
• Are fluent in English

• Experience with robotic manipulation: dexterous grasping, in-hand manipulation, or contact-rich tasks
• Experience with mobile robotics
• Force, impedance, or tactile-feedback control
• Experience modelling soft, compliant, or continuum systems (Cosserat rods, FEM, SOFA, differentiable simulation)
• System identification, actuator modelling, or domain randomisation for sim-to-real
• Teleoperation and demonstration data pipelines, or experience with vision-language-action and robot foundation models
• Embedded and real-time experience (STM32, RTOS, CAN)

Why us?

Soft robotics is one of the few fields where the hardware hasn’t caught up to the vision yet, and the models, controllers, and learned policies haven’t either. Soft bodies are exactly where hand-written models struggle and learning shines, which makes them one of the most interesting open problems in robot learning. You’d be joining early enough to define how we simulate, train, and control everything we build, not inherit someone else’s stack. Competitive compensation, equity, and work that will end up in your portfolio for the rest of your career.

Potential matters more than a perfect CV.

If you’re strong in robot learning or classical control but still growing in the other, and you want to work on robots that haven’t been built before, apply anyway.