Autonomy Engineer – Deep Learning Infrastructure

About the role

Skydio is seeking a Deep Learning Infrastructure Engineer to build and scale the systems that power its autonomous drone technology. You will work across autonomy, embedded, and cloud teams to deliver high‑performance computer‑vision inference and MLOps pipelines.

Key responsibilities

• Develop high‑throughput, low‑latency deep‑learning inference solutions for computer‑vision workloads on diverse hardware platforms.
• Profile vision and vision‑language models, identify bottlenecks, and implement optimization and power‑efficiency improvements.
• Design end‑to‑end MLOps workflows for model deployment, monitoring, and re‑training.
• Create custom GPU kernels and SDKs that enable customers and developers to build autonomous ML workflows.

Required profile

• Hands‑on experience with MLOps, ML inference acceleration, and edge deployment.
• Strong fundamentals in deep learning, computer vision, image and video processing.
• Proven ability to build and manage ML pipelines from data preparation through monitoring.
• Experience with security and compliance requirements in ML infrastructure.

Required skills

• MLOps
• ML inference acceleration/optimization
• Edge deployment
• Deep learning fundamentals
• Computer vision, image processing, video processing
• GPU kernel development
• SDK design
• ML frameworks and libraries