Autonomy Lead

What You'll Do

• Own the end-to-end autonomy system across perception, state estimation, planning, and system behavior
• Define system architecture and make tradeoffs across performance, reliability, and complexity
• Lead engineers and set technical direction for autonomy development
• Work directly in the codebase on critical parts of the stack
• Drive integration across GNC, hardware, and mission planning systems
• Own how perception and ML models are developed, evaluated, and improved using real-world data
• Drive dataset strategy, labeling, and iteration loops to improve system performance
• Evaluate model performance in real-world conditions and close gaps between simulation and deployment
• Define how autonomy is validated across simulation, ground testing, and flight testing
• Debug real-world failures using flight data, logs, and system-level analysis
• Identify gaps in the current system and drive changes needed for reliable deployment
• Set execution standards for autonomy development and delivery

What You'll Bring

• Owned autonomy systems that operated in the real world, not just simulation or research environments
• Strong system-level understanding across perception, estimation, and planning, with depth in at least one area
• Experience training, evaluating, or improving ML models used in real-world robotic or autonomy systems
• Experience working with real-world datasets, labeling pipelines, and model iteration cycles
• Experience taking at least one autonomy system from early development through real-world deployment and iteration
• Strong proficiency in C++ and Python
• Experience working across software, hardware, and flight or field operations
• Ability to make practical tradeoffs under real constraints and deliver working systems
• Experience leading engineers and driving technical direction
• Experience debugging real-world autonomy failures using logs, telemetry, or flight data

Bonus Points If You Have

• 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