Autonomy Engineer - Deep Learning

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 https://www.skydio.com/solutions/energy-and-utilities to first responders https://www.skydio.com/solutions/public-safety, soldiers in battlefield scenarios https://www.skydio.com/solutions/national-security/tactical-isr, and beyond https://www.skydio.com/solutions. 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 aerial robots that can autonomously navigate in unknown environments and deliver operational value to users. If you are excited about real world applications of deep learning and solving difficult problems in computer vision and autonomy, we would love to hear from you. As a Deep Learning Engineer, you will be responsible for training and deploying optimized models to our products for solving challenging problems such as 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. How you'll make an impact: - 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 efficie

Department: R&D; Team: Autonomy