Autonomy Engineer - Deep Learning

Skydio · Defense · San Mateo, CA +1 · R&D

Skydio is seeking an Autonomy Engineer - Deep Learning to train and deploy optimized deep learning models for their autonomous flight systems. The role involves designing, implementing, and deploying computer vision and multimodal deep learning models, leveraging real-world and synthetic data, and optimizing models for low-latency embedded hardware. The position requires an MS or PhD, hands-on experience with deep learning model deployment, and strong coding skills in Python/PyTorch and C++.

What you'd actually do

  1. Design, implement, and deploy computer vision and multimodal deep learning models for Skydio’s autonomy system
  2. Leverage massive amounts of real world video and other sensor data for data mining, curation, labeling, training and evaluation
  3. Leverage large scale and diverse synthetic data to power deep learning algorithms
  4. Leverage state-of-the-art foundation models for knowledge distillation and label efficient learning
  5. Refine and optimize models for low-latency on embedded hardware

Skills

Required

  • M.S. or Ph.D. in computer science, electrical engineering or related discipline
  • Demonstrated hands-on experience designing, training and deploying deep learning models
  • Ability to deliver high quality, well-architected code (Python/PyTorch and preferably, C++)
  • Leverage state-of-the-art academic papers and literature for fast iteration
  • Ability to thrive in a fast paced, collaborative and highly technical team environment
  • Comfortable navigating and delivering within a complex codebase
  • Strong communication skills

What the JD emphasized

  • real-time deep networks
  • low-latency on embedded hardware
  • deep learning models

Other signals

  • real-time deep networks
  • autonomous navigation
  • computer vision
  • deep learning models
  • embedded hardware