The Role
Lead the design and development of solutions for piloted and autonomous aircraft, focusing on technical authority, system architecture, cross-team management, and adherence to aerospace development processes.
Summary Generated by Built In
About us:
Daedalean is a Zürich-based startup founded by experienced engineers who want to completely revolutionize air travel within the next decade. We combine computer vision, deep learning, and robotics to develop full “level-5” autonomy for flying vehicles.
Your role:
To provide technical leadership supporting the design and development of Daedalean’s suite of solutions for piloted and/or autonomous aircraft.
Responsibilities:
- Working with visual and digital sensor technologies, fusion algorithms, situational awareness algorithms, threat assessment, threat risk mitigation, flight guidance, flight computers, and aircraft integration.
- Technical authority over a full development project scope.
- Define system architectures, considering functional hazards and safety requirements.
- Define baselines and manage configuration.
- Manage cross-team interfaces and requirements.
- Manage change.
- Ensure development process adherence.
- Evaluate supplier capabilities and provide recommendations.
- Oversee certification compliance.
- Capture lessons and implement improvements.
- Support the Project Manager with resources leadership, reporting, and risk management.
- Support the development of project schedules.
Preferred Qualifications & Experience:
- Hands-on experience with electronics.
- MS or PhD degree in Aerospace Engineering (guidance), Electrical Engineering (EE), Electrical and Computer Engineering (ECE), or related technical field, or equivalent experience.
- A background in engineering with a strong academic record and a demonstrated ability to convert theory into practice.
- 10+ years of Avionics and/or Flight Controls experience.
- Experience with aerospace development processes: ARP4754A, ARP4761, DO-178C, DO-254.
- Experience with the FAA and/or EASA certification processes.
- Knowledge and/or experience with EASA Concepts for Design Assurance of Neural Networks (CoDANN) and First Usable Guidance (FUG) for Machine Learning Applications is a plus.
- Experience with AI/ML applications is a plus.
Benefits:
- A team of experienced engineers and researchers, who joined us from most recognized companies and institutions.
- Difficult and interesting problems to solve.
- Pilot license subsidy.
- Hybrid work setting.
- Learning & Development budget: visit conferences of your choice.
- Gym membership.
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The Company
What We Do
Daedalean creates safety-critical AI systems for situational awareness and flight control, with the eventual goal of developing certified autonomy in the air.
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