Skydio

The role focuses on building and scaling infrastructure for deep learning and AI efforts, specifically for high-performance inference of computer vision workloads on various hardware platforms. It involves profiling, optimizing, and deploying models, as well as creating MLOps workflows and potentially implementing GPU kernels. The goal is to accelerate progress in intelligent mobile robots by leveraging visual data for semantic and geometric understanding.

The role focuses on building and scaling the infrastructure for Skydio's Deep Learning (DL) and AI efforts, specifically for computer vision (CV) workloads. This includes developing high-performance inference solutions, profiling models, designing MLOps workflows, improving training efficiency, implementing GPU kernels, and creating SDKs for autonomous workflows. The role operates at the intersection of autonomy, embedded, and cloud teams, emphasizing ML inference acceleration, optimization, and edge deployment.

The Autonomy Engineer - Deep Learning Model Acceleration role at Skydio focuses on building and scaling infrastructure for AI/ML efforts, specifically optimizing deep learning inference for computer vision workloads on various hardware platforms. This involves profiling models, designing MLOps workflows, improving training efficiency, implementing GPU kernels, and creating SDKs for autonomous workflows, with a strong emphasis on edge deployment and performance optimization.