Design and implement scalable, extensible, interactive data pipelines and annotation workflows
Build tools that leverage state-of-the-art machine learning systems for efficient data exploration and curation across the fleet of Skydio drones
Design and implement pipelines for data ingestion, versioning, model training, deployment and monitoring
Optimize and scale deep learning training workflows to improve team iteration velocity
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

Demonstrated hands-on experience with data engineering and building large scale, performant and efficient data processing pipelines
Demonstrated hands-on experience with cloud-based ML platforms, containerization technologies, ML Ops platforms and databases
Experience and understanding of security and compliance requirements in ML infrastructure
Demonstrated hands-on experience building and managing ML pipelines including data preparation, model training, model deployment and monitoring
You have demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
You are comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth
Obtaining FAA Part 107 certification within the first 60 days of employment is strongly encouraged for all Skydio employees and required for certain positions.

Autonomy Engineer – ML & DL Infrastructure

Key skills