Autonomy Engineer - Deep Learning Model Acceleration

ph3Autonomy Engineer - Deep Learning Model Acceleration /h3pSkydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best‑in‑class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders, soldiers in battlefield scenarios, and beyond. /ph3About the role /h3pLearning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real‑time deep networks to accelerate progress in intelligent mobile robots. If you are excited about leveraging massive amounts of structured video data to solve problems in Computer Vision (CV) such as object detection and tracking, optical flow estimation and segmentation, we would love to hear from you. /ppAs a deep learning model acceleration engineer, you will be responsible for building and scaling the infrastructure that supports Skydio’s Deep Learning (DL) and AI efforts. You will be working at the nexus of Skydio’s autonomy, embedded and cloud teams to deliver new capabilities and empower the deep learning team. /ph3Responsibilities /h3ulliDevelop solutions for high‑performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms. /liliProfile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads. /liliDesign and implement end‑to‑end MLOps workflows for model deployment, monitoring, and re‑training. /liliUtilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance. /liliCreate new methods for improving training efficiency. /liliImplement GPU kernels for custom architectures and optimized inference. /liliDesign and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML). /liliLeverage your expertise and best‑practices to uphold and improve Skydio’s engineering standards. /li /ulh3Qualifications /h3ulliDemonstrated hands‑on experience with MLOps, ML inference acceleration/optimization, and edge deployment. /liliStrong knowledge of DL fundamentals, techniques, and state‑of‑the‑art DL models/architectures. /liliStrong fundamentals in CV, image processing, and video processing. /liliDemonstrated hands‑on experience building and managing ML pipelines for solving vision or vision‑language tasks including data preparation, model training, model deployment, and monitoring. /liliExperience and understanding of security and compliance requirements in ML infrastructure. /liliExperience with ML frameworks and libraries. /liliAbility to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, deployment, and monitoring. /liliComfortable navigating and delivering within a complex codebase. /liliStrong communication skills and ability to collaborate effectively at all levels of technical depth. /li /ulh3EEO Equal Opportunity Statement /h3pQualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or other characteristics protected by federal, state, or local anti‑discrimination laws. /ppFor positions located in the United States of America, Skydio, Inc. uses E‑Verify to confirm employment eligibility. To learn more about E‑Verify, including your rights and responsibilities, please visit /p /p #J-18808-Ljbffr