Autonomy Engineer - Deep Learning at Skydio

On-site - San Mateo, California, United States

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Autonomy Engineer – Deep Learning. Learn semantic and geometric understanding of the world from visual data to push boundaries of real-time deep networks. Responsible for training and deploying optimized models for optical flow estimation, stereo depth estimation, object detection, segmentation and tracking, visual place recognition, localization and mapping, few-shot learning, occupancy networks, automated path planning, etc. The role involves design, implementation, deployment, data mining, labeling, evaluation, optimization for low-latency embedded hardware, and evaluation benchmarks.

Salary

USD 170,000 - 277,500/year

Requirements

Education

  • M.S. or Ph.D. in computer science, electrical engineering or related discipline

Experience

  • Demonstrated hands-on experience designing, training and deploying deep learning models

Skills

  • 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

Responsibilities

  • Design, implement, and deploy computer vision and multimodal deep learning models for Skydio’s autonomy system
  • Leverage massive amounts of real world video and other sensor data for data mining, curation, labeling, training and evaluation
  • Leverage large scale and diverse synthetic data to power deep learning algorithms
  • Leverage state-of-the-art foundation models for knowledge distillation and label efficient learning
  • Refine and optimize models for low-latency on embedded hardware
  • Develop evaluation benchmarks and metrics to quantify the performance of autonomous systems
  • Be a generalist helping out on all aspects of the software when needed

Technologies

PythonPyTorchC++

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