Autonomy Lead

Join our team as an Autonomy Lead, where you will be responsible for defining and implementing the end-to-end autonomy system for real-world flight. You will lead a small team while staying hands-on in architecture, implementation, and flight debugging. Your work will directly impact the safety and consistency of aircraft missions. This is not an entry-level role; we are looking for someone with experience in building and deploying autonomy systems on real-world robotic or UAV platforms.

• Define and oversee the integration of perception, state estimation, planning, and flight behaviors into a cohesive autonomy system that operates reliably in real-world conditions.
• Lead a small team of engineers in the architecture, implementation, and debugging of critical parts of the autonomy stack, while also being hands-on in the codebase.
• Drive the development and improvement of machine learning models used in the autonomy system, ensuring they perform effectively outside of ideal conditions.
• This is not an entry-level role. We are looking for someone who has already built and deployed autonomy systems on real-world robotic or UAV platforms
• Ability to make practical tradeoffs under real constraints and deliver working systems
• Experience taking at least one autonomy system from early development through real-world deployment and iteration
• Experience training, evaluating, or improving ML models used in real-world robotic or autonomy systems
• Strong proficiency in C++ and Python
• Strong system-level understanding across perception, estimation, and planning, with depth in at least one area
• Experience working with real-world datasets, labeling pipelines, and model iteration cycles
• Experience debugging real-world autonomy failures using logs, telemetry, or flight data
• Experience leading engineers and driving technical direction
• Experience working across software, hardware, and flight or field operations
• You have owned autonomy systems that operated in the real world, not just simulation or research environments
• Experience with autonomous aircraft or aerial systems
• Background in robotics, computer vision, or motion planning
• Experience with real-time or embedded systems
• Familiarity with ROS2 or similar robotics frameworks
• Experience deploying ML models to resource-constrained or real-time systems