Autonomy Software Systems, Simulation, & Infrastructure Engineer

About the role:

The Autonomy Systems team builds the critical infrastructure that powers autonomy development at scale — from simulation systems to developer tooling to log analysis frameworks. We accelerate iteration cycles, unlock deeper insights, and enable safer and more reliable robotics systems across development and deployment.

Our scope spans:

• Simulation systems used internally and externally — enabling high-fidelity testing, scenario replay, and customer-facing virtual environments.
• Developer enablement tools — including log playback and visualization platforms, large-scale log-based regression testing, data mining for machine learning, and system observability dashboards.
• High-leverage research projects — pushing the boundaries of autonomy through rapid experimentation, e.g., reinforcement learning for complex tasks like dock landings.

We work closely with autonomy, systems, and infrastructure teams, providing both foundational components and innovative tools that multiply their impact.

How you'll make an impact:

• Enhancing our in-house simulator to support new product scenarios and complex physical behaviors (e.g., latency injection, rain/GPS simulation).
• Building log visualization and playback tools that are fast, robust, and developer-friendly.
• Supporting data-centric validation pipelines and regression testing across thousands of logs.
• Improving observability and performance monitoring across autonomy systems (CPU, GPU, thermals, etc.).
• Helping drive ML infrastructure efforts (e.g., training data curation, RL environments), if you bring background or interest in the space.

What makes you a good fit:

• 2+ years of professional software engineering experience
• Strong programming skills in C++ and/or Python
• Strong communication skills and the ability to drive technical efforts across team boundaries
• Experience with robotics, autonomous systems, or embedded development
• Solid foundation in systems engineering, including performance optimization and debugging
• Experience building internal tools, infrastructure, or developer-facing platforms
• Familiarity with simulation, virtual test environments, or similar systems
• Comfortable working in a fast-paced, cross-functional environment with evolving requirements
• Background in machine learning tooling, training infrastructure, or RL environments
• Experience with log ingestion, replay systems, or time-synchronized data pipelines
• Experience with web tooling frameworks (e.g., React, Three.js, Plotly, TypeScript) is a plus

Compensation Range: The annual base salary range for this position is $170,000 - 240,000*. 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.

*For some positions the pay may be dependent upon the individual's regional location.

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