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Remote role · autonomy

Autonomy Engineer - Deep Learning Model Acceleration

Skydio

Before you apply

Role details

The practical picture
Employment
Full-time

Inside the role

Qualifications
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 Experience building and managing ML pipelines for vision or vision-language tasks
Role signal brief

The role, at a glance

Extracted from the source posting · 85% confidence

Skydio seeks an Autonomy Engineer to build infrastructure for real-time deep learning inference and MLOps workflows. The role focuses on accelerating computer vision and vision-language models for autonomous drone applications, requiring expertise in GPU optimization, edge deployment, and ML pipeline architecture.

What you need

  • 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
  • Experience building and managing ML pipelines for vision or vision-language tasks

What you will own

  • Develop high-performance deep learning inference solutions for CV workloads with high throughput and low latency across hardware platforms
  • Profile CV and VLMs to identify performance bottlenecks, optimize acceleration opportunities, and improve power efficiency
  • Design and implement end-to-end MLOps workflows for model deployment, monitoring, and re-training
  • Implement GPU kernels for custom architectures and optimized inference
  • Create methods for improving training efficiency
  • Design SDKs enabling customers to build autonomous workflows using ML
Core skills
Deep LearningComputer VisionMLOpsInference OptimizationGPU KernelsEdge DeploymentPythonML FrameworksVideo Processing
Internal freshness window ends Oct 22, 2026
View source evidence
  • summary “Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms”
  • summary “Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency”
  • summary “Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training”
  • location “Job location: Zurich, Switzerland”
  • location “Structured Location: Zurich, Switzerland”
  • must_have “Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment”
  • must_have “Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures”
  • must_have “Strong fundamentals in CV, image processing, and video processing”
  • must_have “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”
  • location “For positions located in the United States of America, Skydio, Inc. uses E-Verify to confirm employment eligibility”
deep learningcomputer visionmlopsinference optimization
Role brief

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 to first responders, soldiers in battlefield scenarios, and beyond.

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 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.

As 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.

How you’ll make an impact:

  • 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

What makes you a good fit:

  • 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

  • You have demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring

  • You are comfortable navigating and delivering within a complex codebase

  • Strong communication skills and the ability to collaborate effectively at all levels of technical depth

#LI-PG1

At Skydio we believe that diversity drives innovation. We have created a multidisciplinary environment that embraces the power of diverse perspectives to create elegant solutions for complex problems. We are committed to growing our network of people, programs, and resources to nurture an inclusive culture.

Qualified 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.

For 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 https://www.e-verify.gov/