Autonomy Engineer - Deep Learning Infrastructure

Stack

Responsibilities

• ▹Develop high-performance deep learning inference solutions for CV workloads with high throughput and low latency across hardware platforms
• ▹Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks, and improve power efficiency
• ▹Design and implement end-to-end MLOps workflows for model deployment, monitoring, and re-training
• ▹Apply advanced ML knowledge to leverage training/runtime frameworks and model efficiency tools
• ▹Create new methods for improving training efficiency
• ▹Implement GPU kernels for custom architectures and optimized inference
• ▹Design and implement SDKs enabling customers/external developers to build autonomous ML workflows

Requirements

• ▹Demonstrated 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
• ▹Demonstrated hands-on experience building and managing ML pipelines (data prep, training, deployment, monitoring)
• ▹Experience with security and compliance requirements in ML infrastructure
• ▹Experience with ML frameworks and libraries
• ▹Demonstrated ability to drive a concept through the full software lifecycle
• ▹Comfortable navigating and delivering within a complex codebase
• ▹Strong communication and collaboration skills at all technical levels

Soft skills

About the company

Skydio is the leading US drone company and the world leader in autonomous flight, combining deep AI expertise with best-in-class hardware and software development to serve a broad range of drone users, from utility inspectors to first responders and military applications.