AI Research Engineer - Reinforcement Learning

apartmentHelsing placeBarcelona calendar_month 

Experteer Overview

Join Helsing to shape autonomous AI for a high-stakes defense platform. You will build and integrate advanced RL agents for real-time flight-ready systems and own the end-to-end pipeline from simulation to deployment. The role sits at the intersection of cutting-edge research and operational autonomy, contributing to a mission-driven team focused on robust, safe, and ethical AI in defence.

You will work on a world-class autonomous aerial platform and impact how intelligent systems operate in challenging environments. This is a unique chance to push state-of-the-art in reinforcement learning within a privacy-conscious, science-led culture.

Compensaciones / Beneficios
  • Develop, train, and deploy reinforcement learning agents into operational, flight-ready systems
  • Lead end-to-end lifecycle from large-scale simulation training to real-time deployment
  • Integrate RL policies with high-performance runtime systems under strict latency requirements
  • Collaborate with cross-functional teams to advance the Centaur project and the CA-1 Europa platform
  • Experiment with modern RL methods and ensure robustness and reliability in real-world operations
Responsabilidades
  • MSc in Reinforcement Learning, Robotics, Automation and Control (or closely related field)
  • Hands-on experience building, training, and deploying RL agents with real-world iteration
  • Strong knowledge of model-free RL (PPO, SAC), multi-agent RL, and long-horizon decision making
  • Experience integrating RL into production AI software with attention to latency and throughput
  • Proficient software engineering in Python and/or Rust/C++, including testing, QA, and monitoring
  • Excellent communication skills to report research findings clearly
  • Active engagement with current research and capability to extend state-of-the-art approaches
Requisitos principales
  • Competitive salary
  • VSOP options
  • Relocation support
  • Learning allowance
  • Health u0026 wellness (gym, mental health support)
  • Parental leave and remote work options
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