Autonomy Engineer - Deep Learning Infrastructure

The role

You will build and scale the infrastructure that supports Skydio's Deep Learning and AI efforts. You will work at the nexus of autonomy, embedded, and cloud teams to deliver new capabilities.

What you will do

• Develop solutions for high-performance deep learning inference for CV workloads
• Profile CV and Vision Language Models to analyze performance and identify bottlenecks
• Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
• Utilize advanced Machine Learning knowledge to improve system performance
• Create new methods for improving training efficiency
• Implement GPU kernels for custom architectures and optimized inference
• Design and implement SDKs for customers and external developers
• Uphold and improve Skydio's engineering standards

Required qualifications

• Hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
• Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
• Strong fundamentals in CV, image processing, and video processing
• Hands-on experience building and managing ML pipelines for vision or vision language tasks
• Experience and understanding of security and compliance requirements in ML infrastructure
• Experience with ML frameworks and libraries
• Ability to drive a concept through the software lifecycle: architecture, development, testing, deployment, and monitoring
• Comfortable navigating and delivering within a complex codebase
• Strong communication skills

About the company

Skydio is the leading US drone company and the world leader in autonomous flight. The team combines expertise in artificial intelligence, hardware and software product development, operational excellence, and customer obsession.