Autonomy Engineer - Deep Learning na Skydio

Presencial - San Mateo, California, United States

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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