Your mission

  • Design and implement swarm behaviors, coordination logic, and distributed autonomy architectures
  • Develop task allocation, role switching, and dynamic replanning strategies for real-time multi-agent systems
  • Use behavior trees, hierarchical planning, and mission execution frameworks to scale swarm decision-making
  • Implement and test reinforcement learning and self-organizing behaviors
  • Integrate with simulation tools and testbed hardware for multi-UAV system testing
  • Collaborate with robotics, perception, and systems engineers to close the loop between swarm-level planning and platform-level control
  • Contribute to scalable mission planning and execution pipelines for real-world deployments

Your profile

  • Strong experience in multi-agent systems or distributed systems
  • Deep understanding of swarm algorithms, coordination, and self-organizing systems
  • Experience with UAV swarming or multi-robot coordination in simulation or field settings
  • Familiarity with behavior trees, finite state machines, or hybrid control architectures
  • Knowledge of ROS / ROS2 in complex robotics environments
  • Proficiency in Python and/or C++ for real-time autonomous systems
  • Experience with mission planning, execution frameworks, and real-time decision-making
Nice to have:
  • Applied work with reinforcement learning in multi-agent or real-time systems
  • Familiarity with UAV teaming concepts from defense, aerospace, or large-scale robotics
  • Hands-on testing in hardware-based drone swarms
  • Experience with dynamic replanning, conflict resolution, and distributed consensus
  • Background in autonomous behavior under uncertainty and adaptive autonomy

Why us?

Do you feel that you fit the description, but don't think you fulfill all the criteria 100%? Apply to us anyway.   
We look forward to receiving your detailed application via our online form.  

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Location

Munich (DEU)

Job Overview
Job Posted:
1 week ago
Job Expires:
Job Type
Full Time

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