Autonomy Engineer - ML & DL Infrastructure

ppSkydio 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. /p h3About the Role /h3 pSkydio is the leading US drone company and the world leader in autonomous flight. We leverage breakthrough AI to create the world’s most intelligent flying machines for use by our enterprise, public safety, defense and other customers. Learning a semantic and geometric understanding of the world from best‑in‑class visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with deep networks, AI and ML to accelerate progress in intelligent aerial robots that can autonomously navigate in unknown environments and deliver operational value to users. As a deep learning infrastructure engineer, you will be responsible for building and scaling the infrastructure that supports Skydio’s DL and AI training efforts. You will be working at the nexus of Skydio’s autonomy and cloud teams to deliver new capabilities and empower AI/ML solutions at Skydio. /p h3How You’ll Make an Impact /h3 ul liDesign and implement scalable, extensible, interactive data pipelines and annotation workflows /li liBuild tools that leverage state‑of‑the‑art machine learning systems for efficient data exploration and curation across the fleet of Skydio drones /li liDesign and implement pipelines for data ingestion, versioning, model training, deployment and monitoring /li liOptimize and scale deep learning training workflows to improve team iteration velocity /li liLeverage your expertise and best‑practices to uphold and improve Skydio’s engineering standards /li /ul h3What Makes You a Good Fit /h3 ul liDemonstrated hands‑on experience with data engineering and building large‑scale, performant and efficient data processing pipelines /li liDemonstrated hands‑on experience with cloud‑based ML platforms, containerization technologies, ML Ops platforms and databases /li liExperience and understanding of security and compliance requirements in ML infrastructure /li liDemonstrated hands‑on experience building and managing ML pipelines including data preparation, model training, model deployment and monitoring /li liYou have demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, deployment, and monitoring /li liYou are comfortable navigating and delivering within a complex codebase /li liStrong communication skills and the ability to collaborate effectively at all levels of technical depth /li /ul h3Equal Employment Opportunity /h3 pQualified 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. /p /p #J-18808-Ljbffr