Autonomy Engineer - ML & DL Infrastructure

About the role

Skydio is the world leader in autonomous flight, using breakthrough AI to create intelligent flying machines for enterprise, public safety, defense and more. The Autonomy Engineer will build and scale the deep‑learning and AI training infrastructure that powers Skydio’s autonomous drones. You will work at the intersection of autonomy and cloud teams to enable new AI/ML capabilities.

Key responsibilities

• 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 Skydio fleet.
• 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 expertise and best‑practices to uphold and improve Skydio’s engineering standards.

Required profile

• Hands‑on experience with data engineering and building large‑scale, performant data processing pipelines.
• Hands‑on experience with cloud‑based ML platforms, containerization technologies, ML Ops platforms and databases.
• Understanding of security and compliance requirements in ML infrastructure.
• Experience building and managing ML pipelines including data preparation, model training, deployment and monitoring.
• Ability to take a concept through architecture, development, testing, deployment and monitoring.
• Comfortable navigating and delivering within a complex codebase.
• Strong communication skills and ability to collaborate at all technical levels.

Required skills

• Data engineering
• Cloud‑based machine learning platforms
• Containerization
• ML Ops platforms
• Databases
• Security and compliance in ML infrastructure
• ML pipeline development (data preparation, training, deployment, monitoring)