AI-driven autonomous robotics and defence systems built in Munich
Autonomous Teaming is a Munich defence-tech company building autonomy software for robotic and UAV systems, with a stack spanning ROS 2, PX4, ArduPilot and a deep computer-vision toolkit (YOLO, DETR, Detectron2). Hiring is overwhelmingly engineering and senior-weighted, and adoption of Kubernetes, LiDAR and ROS alongside ISO 27001 and endpoint-security work suggests a shift from R&D prototypes toward hardened, compliance-ready production systems.
Notable leadership hires: Director of Engineering
Autonomous Teaming develops AI-enabled defence systems aimed at countering asymmetric threats, with a focus on autonomous robotics, multi-agent coordination and dual-use technology. Engineering work covers perception models in PyTorch and C++, flight-control integration with PX4 and ArduPilot, and simulation and synthetic-data pipelines. The company runs across Azure, AWS and GCP with Terraform and Ansible, and manages ML experiments through ClearML and MLflow. It is privately held, employs 51–200 people, and is headquartered in Munich, Germany.
Core tools include PyTorch, Python, C++, ROS 2, PX4, ArduPilot, YOLO, DETR and Detectron2, with Docker, Terraform and Ansible across Azure, AWS and GCP, plus ClearML and MLflow for ML ops.
Yes. Hiring is heavily engineering-focused and skewed toward senior talent, with a Director of Engineering among leadership openings. All roles are based in Germany.
Active projects include synthetic data generation pipelines, core autonomy for next-generation robotic systems, multi-agent coordination algorithms, simulation workflow automation and UAV subsystem assembly.
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Autonomous Teaming's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.