PhD Autonomy Engineer Intern - Planning & Controls (Reinforcement Learning)

About the role

Skydio builds the world's most advanced autonomous drones used across inspection, public safety, defense, cinematography, and more. Develop and deploy reinforcement learning and adjacent policy-learning methods that make Skydio aircraft plan, navigate, and control themselves more intelligently—safely, reliably, and efficiently—across our ecosystem: handheld apps, ground control, cloud autonomy services, and fleet workflows.

How you'll make an impact

• Navigation & avoidance in the wild: Train policies that adapt online to cluttered 3D scenes (forests, bridges, urban canyons), complementing geometric stack for robust obstacle avoidance and dynamic goal-seeking.
• RL-augmented planning: Fuse learned cost shaping / value functions with trajectory optimization for smooth, agile flight with tight safety envelopes and mission constraints.
• Sim → Real at scale: Build scalable datasets and training loops with Isaac Lab and domain randomization.