Generally Awesome Engineer

Flight Software, Computer Vision and AI /
Full-Time /
Your Role:

To come up with algorithms and code to completely and reliably replace the human pilot, only bound by the laws of Nature and rules of the air.

You are smart, get stuff done, have min. 5 years of hardcore C++ software engineering experience and one of the below:

    • proven research skills,
    • proven applied engineering skills.

You are witnessed in at least one of the following areas:

    • Systems, embedded or low-level programming, e.g. porting netbsd to the bf531, a load balancer for a 12-datacenter spread web service serving 300k qps,
    • Games or graphics programming, e.g. high performance photorealistic rendering,
    • Machine learning, e.g. designing, implementing and evaluating neural networks, generative adversarial networks, fundamental research on xNNs, interpretability, training methods, convergence, etc.,
    • Computer vision, e.g. SLAM and localization systems,
    • Optimizing code for GPUs, FPGA programming, e.g. tweaking code to get the most out of (super)computing facilities,
    • Robotics and control, e.g. motion planning in the air or on the ground, sensor fusion, real time solving of inverse kinematic equations,
    • General or commercial aviation, e.g. flying for fun or profit,
    • Leading or building software engineering teams,
    • Physics, any physics.

    • Experience in aerospace engineering or avionics is not required; we will teach you everything you need to know about the constraints of safety critical systems in airworthy applications.


    • Combine the best of both worlds; a) work in fast-growing startup and b) collaborate with and learn from very experienced engineers and scientists that have previously worked at Google, SpaceX, Apple, Nvidia, CERN, and Rolls Royce,
    • Build cutting-edge technology that will shape our future,
    • Join our pilots to test your ideas in the air during test flights in the Swiss Alps,
    • Develop scarce and marketable skills in the fields of safety-critical avionics systems development, computer vision, machine learning, and robotics.