Autonomy Engineer Intern - Deep Learning (computational Photography)

Skydio Skydio · Defense · Zurich, Switzerland · R&D

The role focuses on designing, implementing, and deploying deep learning models for autonomous flight systems, with a specific emphasis on computational photography applications. It involves training and optimizing models for both embedded hardware and cloud deployment, using real-world and synthetic data, and developing evaluation benchmarks.

What you'd actually do

  1. Design, implement and deploy deep learning models with a particular focus on computational photography applications such as super-resolution, multi-frame denoising, low light imaging, High Dynamic Range (HDR) imaging etc.
  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

Nice to have

  • C++

What the JD emphasized

  • deep learning models
  • computational photography
  • training and deploying optimized models
  • low-latency on embedded hardware

Other signals

  • real-time deep networks
  • deep learning models
  • computational photography
  • autonomous flight