Technical Lead of Software Autonomy

Quantum-Systems GmbH
München, Germany
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Artificial Intelligence Python (Programming Language) Machine Learning Tensorflow Software Engineering Systems Architecture Pytorch Machine Learning Operations TensorRT C++14 GNSS

Job description

As the Technical Lead of Autonomy SW - Land Domain, you will shape the next generation of autonomous ground systems by bringing state-of-the-art AI and robotics research into production. You will define the technical direction and lead the design and implementation of our autonomy stack, spanning both classical modular architectures and modern end-to-end learning approaches.

Working hands-on with a team of exceptional engineers, you will transform cutting-edge autonomy research into robust, production-ready capabilities that enable autonomous systems-from unmanned ground vehicles (UGVs) to autonomous trucks-to operate safely, reliably, and at scale across complex environments, including GNSS-denied areas, challenging off-road terrain, structured on-road networks, and coordinated multi-vehicle missions.

You will work closely with Product Management and experts across software, hardware, AI, and mission systems to identify the right combination of sensors, algorithms, and system architectures for each challenge. As a technical leader, you will shape the engineering direction of autonomy within the Land Domain, foster engineering excellence, and help establish Quantum Systems as a leader in next-generation autonomous systems.

What is your Day to Day Mission:

  • Lead the creation of the next generation of autonomous systems, translating advances in AI and robotics into production-ready capabilities
  • Drive collaboration of multi-disciplinary engineering teams across perception, control, estimation, and simulation, taking ultimate accountability for domain deliverables and field readiness.
  • Proactively enable engineering teams by identifying and securing necessary hardware, sensors, compute platforms, synthetic data environments, and real-world testing infrastructure before bottlenecks occur.
  • Ensure high-level ML models (learned planners, world models) run safely, reliably, and deterministically under real-time edge constraints.
  • Drive cross-domain alignment with Hardware, Platform, and Mission Systems teams to guarantee seamlessly integrated physical vehicles., * Work-life Balance: We offer flexible work schedules, and 30 days of paid vacation each year to support your personal and professional life.

  • Lunch Benefit: We promote healthy eating and the well-being of our employees with a monthly lunch budget.

Requirements

  • Proven track record of building and shipping production-grade autonomous systems based on modern AI approaches.
  • Deep understanding of both classical autonomy architectures (perception, localization, planning, and control) and modern end-to-end approaches, with the ability to choose the right solution for the problem.
  • Extensive experience designing and optimizing large-scale ML systems for deployment under real-world constraints such as latency, compute, reliability, and safety.
  • Strong software engineering skills in modern C++ (and/or Rust) and Python (PyTorch, Tensorflow), including TensorRT with a passion for writing clean, maintainable, and production-ready code.
  • Ability to translate cutting-edge research into practical engineering solutions and rapidly evaluate new technologies.
  • Outstanding systems thinking and architectural skills, balancing innovation with robustness and long-term maintainability.
  • Demonstrated technical leadership through mentoring, architectural guidance, and leading complex engineering initiatives.
  • Ownership mindset with a history of driving ambitious technical visions from research and prototypes to successful field deployment.
  • Excellent communication skills and the ability to collaborate effectively across AI, robotics, software, hardware, and product teams.
  • Comfortable communicating in English in an international engineering environment.

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