STARK

Senior Software Engineer - Mission Autonomy (All Genders)

Stellenbeschreibung:

Senior Software Engineer - Mission Autonomy (All Genders)

STARK is a new kind of defence technology company revolutionizing the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective. This provides our operators with a decisive edge in highly contested environments. We're focused on delivering deployable, high-performance systems - not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe - today. We move fast, ship real software, and operate under constraints most engineers never encounter - low-bandwidth networks, air-gapped devices, high-stakes decision loops. There is no room for abstraction for its own sake. Everything we build ends up in the hands of real operators in the field . Our Team is dedicated to a mission of pure strikes. As an Senior AI Systems Engineer with a focus on Robotics and Swarming, you will play a critical role in defining the tactical brain and behavioral logic onboard next-generation autonomous drone swarms. Rather than focusing on computer vision, you will work directly with advanced behavioral frameworks, multi-agent reinforcement learning, and high-fidelity simulation environments to build robust, scalable decision-making functionality. You will contribute as a highly skilled individual contributor-hands-on with the system-bridging the gap between machine learning models and physical flight controls, ensuring swarms can dynamically reason and coordinate in real-time. Your work will be essential to ensuring that our autonomous systems operate reliably in real-world, unpredictable environments. Design, train, and deploy decision-making frameworks using RL, imitation learning, and behavior-tree architectures for coordinated behavior across our fixed-wing, tube-launched, and quadcopter platforms. Develop and optimize algorithms for decentralized task allocation, collective intelligence, and multi-vehicle strategic coordination under communication-constrained or GPS-denied conditions - building on our existing TDOA/RSSI localization and mesh networking work. Build and heavily utilize ROS2 SITL environments to stress-test behavioral logic, neural networks, and reactive behaviors before hardware deployment, extending our current simulation-phase epic (containerized comms, leader-follower scaling). Engineer pipelines to move trained models and policies off the GPU cluster and onto edge robotics hardware without performance degradation, feeding directly into our hardware-phase epic (mesh networking with real drones, end-to-end flight test). Collaborate closely with the perception and flight control teams to ensure AI-driven behaviors interface cleanly with safety-critical C++ flight software. Profile and debug behavioral system performance under embedded constraints, ensuring stability and robustness in field deployments across all three platform types. Contribute to system-level architecture discussions on autonomous decision-making, heuristic planning, and multi-agent reliability. Master's or Ph.D. in Robotics, Computer Science, Aerospace Engineering, or related field with emphasis on autonomous decision-making. 3+ years professional or advanced research experience in Robotics AI, multi-agent reinforcement learning, or autonomous behavioral modeling. Strong programming proficiency in Python and C++ for embedded and robotics development; comfort working alongside safety-critical flight code. Mastery of SITL workflows to validate neural networks and decision-making logic under variable, adversarial, or degraded-comms conditions. Deep theoretical and practical knowledge of MDPs, game theory, heuristics, and trajectory/motion planning, applicable to strike-capable UAV coordination. Proven track record moving ML models from simulation to physical edge-robotics systems - ideally on multi-vehicle or swarm platforms rather than single-agent robotics. Strong debugging skills in real-time, resource-constrained environments. Effective communicator able to work across autonomy, hardware, and flight-software disciplines. Willingness to travel occasionally for field testing and deployment. For further information please reach out to Sally Grütte-Pad, Interim Lead TA Partner via

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Confirmed H-1B sponsor. The Department of Labor record shows filings under STARK ASSOCIATES LLC .

Filings 124

Approved 99.2%

Avg wage $71K

From public Department of Labor LCA disclosures. Sponsorship history is a signal about the employer, not a commitment on this role.

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Stelleninformationen

  • Veröffentlichungsdatum:

    25 Aug 2026
  • Standort:

    München

    Einsatzort:

    Munich
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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