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Autonomy Engineer - Deep Learning Infrastructure

Skydio· R&D
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Hybrid (Zurich, Switzerland)Full-timePosted 5mo ago

About the role

Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of real-time deep networks to accelerate progress in intelligent mobile robots. Build and scale the infrastructure that supports Skydio’s DL/AI efforts and empower the deep learning team across autonomy, embedded, and cloud.

Responsibilities

  • Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
  • Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads
  • Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
  • Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
  • Create new methods for improving training efficiency
  • Implement GPU kernels for custom architectures and optimized inference
  • Design and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML)
  • Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

Qualifications

  • Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
  • Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
  • Strong fundamentals in CV, image processing, and video processing
  • Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment, and monitoring
  • Experience and understanding of security and compliance requirements in ML infrastructure
  • Experience with ML frameworks and libraries
  • Ability to take a concept and drive it through the software lifecycle: architecture, development, testing, deployment, and monitoring
  • Comfort navigating and delivering within a complex codebase
  • Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Skills

Required:MLOpsDL fundamentalsCV / image processingML pipelinesML frameworks/libraries
Nice to have:security and compliance

Benefits

  • (Not specified in the description)
Last updated Jul 16, 2026. Interested? Apply on the company site.
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About Skydio

A family of flying robots.

AI-powered autonomous drones for Drone as First Responder (DFR), critical infrastructure inspection, tactical ISR, site security, surveying and mapping

DronesAutonomous SystemsInspectionSecurityMappingPublic SafetyNational Security
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