Skydio

Drones

AutonomyEngineer-ML&DLInfrastructure

Zurich, Switzerland FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Autonomy Engineer - ML & DL Infrastructure at Skydio. Skills: ML Infrastructure, Data pipelines, ML Ops. Design and implement scalable, extensible, interactive data pipelines. Annotation workflows”

What You'll Achieve.

Deliver new capabilities; Empower AI/ML solutions

Industry & Context.

Drones
Problems you'll solve

Solve open problems

Eligibility Requirements

Obtaining FAA Part 107 certification within the first 60 days of employment is strongly encouraged for all Skydio employees and required for certain positions

What They're Looking For.

Must Have

Demonstrated hands-on experience with data engineering, Building large scale, performant and efficient data processing pipelines, Demonstrated hands-on experience with cloud-based ML platforms, Containerization technologies, ML Ops platforms, Databases, Experience and understanding of security and compliance requirements in ML infrastructure, Demonstrated hands-on experience building and managing ML pipelines, Data preparation, Model training, Model deployment, Monitoring, Demonstrated ability to take a concept and systematically drive it through the software lifecycle, Architecture, Development, Testing, Deployment, Monitoring, Comfortable navigating and delivering within a complex codebase

Nice to Have

Obtaining FAA Part 107 certification within the first 60 days of employment is strongly encouraged

What You'll Do.

Design and implement scalable

interactive data pipelines

Build tools for efficient data exploration

Curation across the fleet of Skydio drones

Design and implement pipelines for data ingestion

Optimize and scale deep learning training workflows

Improve team iteration velocity

Uphold and improve Skydio’s engineering standards

How You'll Work.

Team & Collaboration

Working at the nexus of Skydio’s autonomy and cloud teams; Collaborate effectively at all levels of technical depth

Communication Scope

Communication skills

Full Job Description

Skydio 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 https://www.skydio.com/solutions/energy-and-utilities to first responders https://www.skydio.com/solutions/public-safety, soldiers in battlefield scenarios https://www.skydio.com/solutions/national-security/tactical-isr, and beyond https://www.skydio.com/solutions. About the Role: Skydio 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. If you are excited about leveraging massive amounts of structured video data to solve open problems in object detection and tracking, optical flow estimation and segmentation, we would love to hear from you. 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. How You’ll Make an Impact: - Design and implement scalable, extensible, interactive data pipelines and annotation workflows - Build tools that leverage state-of-the-art machine learning systems for efficient data exp

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