Helsing is a defence AI company.
Helsing is a defence AI company.
As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI.
We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.
You will be part of a team pushing the boundaries of autonomous robotics through reinforcement learning.
Your work will focus on designing, training and deploying RL-based controllers for robots operating in complex, unstructured, and dynamic real-world environments — where classical control approaches fall short.
This includes enabling robots to perceive and understand their surroundings by fusing rich sensory inputs, including vision, to inform robust and adaptive control.
You will own the full pipeline from simulation to deployment, ensuring that learned policies are robust, efficient, and ready for real-world operation under tight hardware constraints.
Hold an MSc or PhD in Robotics, Machine Learning, Control Engineering, or a closely related field, with a strong focus on reinforcement learning and robot control.
Have hands-on experience training and deploying RL-based controllers on real robotic hardware, not just in simulation — you have seen your policies fall, iterate, and ultimately succeed on a physical system.
Are deeply familiar with modern RL techniques for continuous control, including but not limited to: model-free methods (PPO, SAC, TD3), model-based RL, hierarchical RL, sim-to-real transfer strategies, domain randomisation, and curriculum learning.
MuJoCo, Isaac Gym/Isaac Lab, PyBullet, Gazebo) for training and validating RL policies.
Possess solid software engineering skills,



writing clean and well-structured code in Python and/or languages like Rust or modern C++, and have experience deploying AI software to production including testing, QA, and monitoring.
Note: We operate at an intersection where women, as well as other minority groups, are systematicallyunder-represented.
PhD in Robotics, Reinforcement Learning, Control Engineering, or related fields, with publications in top-tier venues (e.g. Experience developing controllers for highly dynamic robotic systems operating under complex contact interactions and demanding environmental conditions.
Experience with vision-based perception for robotics control, such as depth estimation, visual odometry, or visuomotor policy learning.
Familiarity with low-level motor control interfaces and real-time embedded systems constraints.
Experience with online adaptation and meta-learning techniques to enable robots to adapt to changing environmental conditions
Experience with sensor fusion (IMU, proprioception, exteroception, vision) to inform and enhance learned control policies.
You will face unique Engineering and AI challenges that make a meaningful impact in the world.
Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure.
Relocation support: up to €2,500 and 4 weeks temporary accommodation
Social: regular company events and monthly social allowances
5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.

📌 Robotics & Control Engineer (Barcelona)
🏢 Helsing
📍 Barcelona