DeepScale sparked the tiny deep neural network revolution with SqueezeNet. Based in Mountain View, CA, the company develops AI perception software for advanced driver-assistance and autonomous driving, with a focus on implementing efficient neural networks on automotive-grade processors.
DeepScale uses deep learning to build accurate and efficient perception systems that enable automated machines to "see". Our software takes input from sensors and produces an environmental model of the real world. Our work has produced neural nets that maintain state-of-the-art accuracy but are up to 500x smaller than other nets designed for the same task. We have thought leaders and experienced practitioners in computer vision, AI-powered 3D reconstruction, and deploying small neural nets in embedded applications.
Planning and Controls Engineer
DeepScale is looking for a planning and controls engineer to develop the planning and actuation modules within DeepScale's products. Your main job responsibilities will be to create a path planning and actuation system for applications like lane centering, AEB, and ACC.