Autonomous Drones Engineer

This role covers the guidance, navigation and control of a pilotless hydrogen airship. It asks for solid control theory and flight dynamics, plus the ability to turn models into working code for onboard flight computers. A strong candidate has a few years of GNC work on a drone, aerospace or automotive product, and is just as happy debugging sensors and drivers on the airfield as tuning control laws in Simulink.

How it fits the AI era

The data the airships collect is turned into defect and leak findings by AI, but this role sits on the flying side, where safe and predictable control matters most. AI tools can speed up simulation, code writing and flight data review, yet the choices about safety, degraded modes and proof for regulators stay with engineers. Judgment during field tests is also very much a human job.

How it builds AI experience

The role itself is mostly classical control and embedded work, so direct AI experience would come from working next to the team that builds the inspection models on LiDAR, imagery and methane data. Someone could build more by using flight logs to spot patterns in how the airship behaves, and by learning how data quality from sensors affects what the detection models can find.

Worth showing

• Simulink control law design
• C/C++ and Python code
• PX4 and MAVLink experience
• Flight data analysis

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About HyLight

Autonomous, hydrogen-powered airships for zero-emission aerial inspection of critical energy and transport grids.