Autonomy Engineer (ML & DL Infrastructure)

Role Overview

Join Skydio as an Autonomy Engineer (ML & DL Infrastructure). You will build and scale the infrastructure that enables Skydio’s deep learning and AI training efforts, partnering with autonomy and cloud teams to deliver new capabilities.

Key Responsibilities

• Design and scale ML/DL data infrastructure, including scalable and extensible data pipelines and workflows (e.g., annotation pipelines).
• Build tools for data exploration and data curation.
• Optimize and scale deep learning training workflows to improve team iteration speed.
• Deliver across the software lifecycle: architecture, development, testing, deployment, and monitoring.
• Uphold engineering standards while working within a complex codebase.
• Ensure security and compliance requirements are met for ML infrastructure.

Requirements

• Hands-on experience in data engineering and building large-scale, performant data processing pipelines.
• Hands-on experience building and operating ML pipelines, including:
  • data preparation
  • model training
  • model deployment
  • monitoring
• Strong communication and collaboration across different levels of technical depth.
• Experience with cloud-based ML platforms, containerization, MLOps platforms, and databases.
• Ability to drive ideas through architecture → development → testing → deployment → monitoring.

Nice-to-Haves / Encouragement

• FAA Part 107 certification within the first 60 days (strongly encouraged; required for certain positions).