Autonomy Engineer Intern, Simulation & Robotics, 2027 (HQ)

Skills this role screens for

About the role

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors https://www.skydio.com/solutions/energy-and-utilities to first responders https://www.skydio.com/solutions/public-safety, soldiers in battlefield scenarios https://www.skydio.com/solutions/national-security/tactical-isr, and beyond https://www.skydio.com/solutions.

The work

ABOUT THE ROLE

The core of our system is the computer vision algorithms that allow drones to understand the world around them. You will architect and implement the algorithms that run on every drone powered by Skydio as part of a world class computer vision and deep learning team with researchers who have pushed the state of the art in academia and industry.

As a Research Intern, you will be paired up with one or more members of our core software development team, assuming direct ownership of a project that meaningfully advances the capabilities of our team and products.

If you have a strong foundation in math, theory, and software development and you are interested in directly contributing to the development of the next generation of autonomy algorithms and pushing them into real products, we would love to hear from you.

The work

AREAS OF RESPONSIBILITY

• Core Simulator Architecture: Design, implement, and evolve the foundational architecture of the Skydio Simulator, ensuring it scales across vehicle types, environments, and use cases.
• Physics and Dynamics: Improve and extend physics models governing vehicle motion, interactions with the environment, and dynamic agents.
• Sensor and Hardware Simulation: Build high-fidelity simulations of cameras, IMUs, and other onboard components, including timing, noise characteristics, and hardware behavior.
• Autonomy Stack Integration: Run and validate the full Skydio autonomy stack in simulation, ensuring consistency between simulated and real-world behavior.
• Feature Development on Top of the Core: Implement simulator capabilities that unlock new workflows for customers and internal autonomy engineers, from training scenarios to advanced testing modes.
• Performance and Fidelity: Profile, optimize, and improve simulator performance while continuously pushing realism and accuracy.

The work

WHAT YOU’LL DO

• Develop core simulator components in C++ and Python, working close to real-time constraints.
• Collaborate with autonomy, perception, and controls engineers to align simulation behavior with real-world systems.
• Debug complex interactions between physics, sensors, autonomy logic, and rendering.
• Help shape the long-term technical direction of the simulator as both a product and an internal platform.
• Contribute to documentation and shared understanding of how the simulator works internally.

Who they want

QUALIFICATIONS

• Strong software engineering experience with C++ and Python.
• Experience building complex systems where performance, determinism, or correctness matter.
• Comfort reasoning about time-synchronized systems, state machines, or real-time execution.
• Ability to work in a large, evolving codebase with multiple stakeholders.
• Interest in robotics, simulation, or physical systems (prior robotics experience is a plus, not a requirement).

Nice to have

BONUS EXPERIENCE

Compensation: The hourly rate for this position is $47/hr for Undergrad, $53/hr for Masters, and $70/hr for PhD students*. Compensation will vary based on factors, including skill level, pr

• Robotics, simulation, game engines, or real-time systems.
• Physics engines, sensor modeling, or hardware abstraction layers.
• Multithreaded or low-latency system design.
• Experience debugging systems that span software and physical behavior.