Senior AI Systems Engineer (Robotics)

Location: Munich or Berlin, Germany

Company

hirify.global designs, develops, and manufactures software-defined unmanned systems for defence applications across multiple operational domains.

What you will do

• Design, train, and deploy decision-making frameworks using reinforcement learning, imitation learning, and behavior trees for coordinated fixed-wing, tube-launched, and quadcopter systems.
• Develop decentralized task allocation, collective intelligence, and multi-vehicle coordination algorithms for communication-constrained and GPS-denied environments.
• Build and use ROS2 SITL environments to test behavioral logic, neural networks, and reactive behaviors before hardware deployment.
• Move trained models and policies from GPU clusters to embedded robotics hardware without performance degradation.
• Integrate AI-driven behaviors with safety-critical C++ flight software and collaborate with perception and flight-control teams.
• Profile and debug autonomous systems under embedded constraints and contribute to architecture for planning and multi-agent reliability.

Requirements

• Master’s or Ph.D. in Robotics, Computer Science, Aerospace Engineering, or a related field focused on autonomous decision-making.
• 3+ years of professional or advanced research experience in robotics AI, multi-agent reinforcement learning, or autonomous behavioral modeling.
• Strong Python and C++ programming skills for embedded and robotics development.
• Deep knowledge of Markov decision processes, game theory, heuristics, and trajectory or motion planning.
• Experience transferring machine-learning models from simulation to physical edge-robotics systems, preferably multi-vehicle or swarm platforms.
• Strong debugging skills in real-time, resource-constrained environments and willingness to travel occasionally for field testing and deployment.

Culture & Benefits

• Hands-on work on deployable autonomous systems used by operators in the field.
• Engineering in challenging environments including low-bandwidth networks, air-gapped devices, and high-stakes decision loops.
• Collaboration across autonomy, hardware, perception, and flight-software disciplines.
• Permanent full-time employment.