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.

You will have the unique opportunity to shape the future of AI in one of the most challenging sectors, where performance needs to be paired with high generalisation capabilities and strong robustness against adversarial attacks. You will develop and integrate state-of-the-art reinforcement learning agents into the operational systems of our own Unmanned Combat Aerial Vehicle, the CA-1 Europa, as part of the groundbreaking Centaur project. This is a unique opportunity to take ownership of novel autonomous systems designed from the ground up, owning the full pipeline from large-scale simulation training through to real-time deployment on flight-ready hardware.

Hold a MSc in Reinforcement Learning, Robotics, Automation and Control, or a closely related field, with a strong focus on sequential decision-making and autonomous systems. Have hands-on experience building, training, and deploying reinforcement learning agents. You have iterated on a policy beyond simulation and understand what it takes to make learned behaviour reliable in a real operational system.

PPO, SAC), population-based training, handling of partial observability and long horizons. Have experience integrating RL policies into high-performance runtime systems, with a solid understanding of the latency and throughput constraints that come with real-time autonomous decision-making. 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.





Have excellent communication skills and the ability to report and present research findings clearly and efficiently, both internally and externally. Are passionate about keeping up to date with current research and enjoy reimplementing and extending state-of-the-art approaches in deep reinforcement learning.

Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. PhD in Reinforcement Learning, Multi-Agent Systems, Automation and Control, Robotics, or a related field, with publications in top-tier venues.

Experience with large-scale distributed RL training frameworks, the infrastructure challenges of running thousands of parallel simulation environments, and gpu-based simulators.

Experience modelling and training multi-agent controllers using state-of-the-art techniques, including emergent coordination, competitive self-play, or decentralised execution with centralised training. Familiarity with flight dynamics, aerospace systems, or guidance, navigation, and control (GNC) concepts.

Experience deploying AI software to safety-critical production systems, including formal verification, testing pipelines, and runtime monitoring. 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. We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it.

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.

📌 Autonomous Flight Rl Research Engineer (Cataluña)
🏢 Helsing
📍 Cataluña