Autonomy Engineer Intern: RL & Flight Control

Skydio, Inc.; Zürich; Hybrid; CHF 54,000 - 80,000; Full time

Job summary

Skydio, Inc. is seeking a PhD candidate for an internship focused on reinforcement learning for autonomous drones.

You will develop RL-based planning and control methods, build scalable sim-to-real pipelines, and collaborate with perception, mapping, and controls teams to deliver real-world advances. Applicants should have strong RL, motion planning, and robotics simulation experience, plus Python proficiency and knowledge of C++/CUDA.

Qualifications

• PhD student in Robotics, ML, Controls or related field.
• Strong fundamentals in RL, control theory, and motion planning.
• Proficient in Python (PyTorch/JAX/Ray RLlib) and at least one of C++ or CUDA.
• Hands-on robotics simulation experience with Isaac Lab, MuJoCo or PyBullet.
• Experience training/deploying policies for navigation/manipulation on robots or autonomous vehicles.

Responsibilities

• Develop and deploy RL and policy-learning methods for Skydio aircraft.
• Train policies to plan, navigate, and control in 3D environments.
• Build scalable sim-to-real workflows and safety filters.
• Collaborate across perception, mapping, controls, and product teams.
• Advance multi-agent coordination and decentralized training for fleet ops.

Skills

Reinforcement Learning

Control Theory

Motion Planning

Python

C++

CUDA

Sim2Real

Multi-Agent RL

Education

PhD student in Robotics, Machine Learning, Controls, or related field

Tools

Isaac Lab

MuJoCo

PyBullet

PyTorch

JAX

RLlib

Job description

Skydio, Inc. is seeking a PhD candidate for an internship focused on reinforcement learning for autonomous drones.

You will develop RL-based planning and control methods, build scalable sim-to-real pipelines, and collaborate with perception, mapping, and controls teams to deliver real-world advances. Applicants should have strong RL, motion planning, and robotics simulation experience, plus Python proficiency and knowledge of C++/CUDA.