Autonomy Engineer Intern, Autonomy Infrastructure, Systems and Tools, 2027 (HQ)

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.

Areas of Responsibility:

• Design and build robust replay and analysis systems that enable engineers to inspect and reproduce recorded autonomy behavior, with fine-grained control over system state, perception outputs, and decision-making at every stage of the stack.

• Develop scalable infrastructure for automated testing and failure triage, expanding our simulation and log-driven test coverage while accelerating root-cause analysis through automated log processing and diagnostics.

• Operate at the interface between autonomy software and core robotics middleware, defining clear APIs, data contracts, and performance requirements for messaging, state propagation, and coordination across subsystems, while partnering closely with downstream teams to support their implementation and integration.

• Design and implement high-quality developer infrastructure and tools that prioritize reliability, performance, and usability, enabling rapid iteration, safe experimentation, and sustained velocity across the autonomy organization.

What You’ll Do:

• Lead the design and implementation of scalable tools used across autonomy development and testing workflows.

• Collaborate with autonomy, QA, and infrastructure teams to gather requirements, align on priorities, and deliver impactful tooling.

• Build tools that streamline stages of the robotics development process.

• Take ownership of internal services from concept through deployment and monitoring.

• Contribute to the long-term vision and roadmap for developer tools that improve debugging efficiency, test coverage, and system understanding.

Qualifications:

• Proficiency in C++ and Python, with a strong grasp of performance-sensitive and multi-threaded systems.

• Experience with simulation frameworks, time-synchronized data systems, or state-machine-driven applications.

• Familiarity with structured data visualization, log processing, or developer tooling design.

• Strong communication skills and the ability to partner effectively with cross-functional teams.

• Comfort operating in a fast-paced environment where requirements evolve and priorities shift.

Bonus Experience:

• Experience building performance-sensitive systems (profiling, multithreading, real-time constraints) in robotics, aerospace, automotive, or similar domains.

• Exposure to robotics / simulation / physics engines.

• Background in telemetry systems, log ingestion pipelines, or automated test environments.

• Front-end development skills in modern web frameworks (e.g., React, TypeScript, Three.js, Plotly) with a focus on data interaction and visualization.

• Familiarity with distributed systems or cloud-hosted services used to support internal tools and customer applications.

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, proficiencies, transferable knowledge, and experience. In addition to base salary, Skydio full-time employees are eligible to enroll in our benefit plans and take advantage of a variety of incentives and stipends.

*Compensation for certain positions may vary based on the position's location.

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