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.


  • You must have worked on applications like LKA (Lane Keeping Assist), LC (Lane Centering) and ACC (Automatic Cruise Control) in an OEM or Tier-1, where you took the output of dynamic environmental model and produced actuation outputs on the CAN bus.
  • The technology you developed must have been used in mass produced vehicles or at least in prototype vehicles. Bonus points if your vehicle passed NCAP tests.
  • Fluent in PID controller theory and coding.
  • Excellent C/C++ coding skills.
  • Experience with CAN bus.
  • Experience in working with drive-by-wire systems.
  • Experience actuating steering columns and braking systems using CAN bus.
  • Bachelors/Masters/PhD in CS, EE, ME, Physics, Mathematics, or similar disciplines.

Bonus points

  • Experience developing safety critical code and being able to follow functional safety processes.