About the position
Daedalean is a Zürich-based startup with US HQ in Phoenix, Arizona. We were 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 involves coming up with algorithms and code to completely and reliably replace the human pilot, only bound by the laws of Nature, Civil Aviation, and budget. You will use machine learning to develop safety-critical algorithms and software for visual guidance, navigation, and control of aircraft, based on your own experience of flight and software engineering. You will contribute to projects spanning both commercial and defense applications, ensuring compliance with industry standards and government regulations while working on cutting-edge aviation technologies.
Responsibilities
- Develop algorithms and code to replace the human pilot.
- Use machine learning to create safety-critical algorithms for visual guidance, navigation, and control of aircraft.
- Contribute to projects in both commercial and defense applications.
- Ensure compliance with industry standards and government regulations.
- Work on cutting-edge aviation technologies.
Requirements
- PhD degree in Computer Science in the field of Artificial Intelligence, Computer Vision, or Machine Learning.
- More than 5 years of high-level C++ software engineering experience in an industry environment.
- In-depth practical and theoretical understanding of machine learning application and implementation.
- Business fluency in English.
- US citizenship is mandatory.
Nice-to-haves
- Experience in aerospace engineering or avionics.
Benefits
- Generous medical, dental and insurance plan.
- 401(k) retirement plan includes employer matching contributions.
- Having an impact on the nascent autonomous flight sector.
- A team of experienced engineers and researchers from recognized companies and institutions.
- Difficult and interesting problems to solve.
- Private Pilot License (PPL) subsidy.
- Hybrid work setting.
- Learning & Development budget.
