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.

Functional Safety Manager

DeepScale is looking for a functional safety manager who is well versed in leading and managing the functional safety process and functional safety audit for our perception software. You will be working with our software developers, who have already started implementing parts of ASPICE process, and you will help the developers with the rest of the process. You will also manage our audit and our gap analysis. Beyond this, you will set up our ASIL-B certification processes and you will also be interfacing with our customers on safety matters.

This position reports directly to the VPE and is a position of high visibility and leverage within the company. We are looking for someone exceptional and passionate both about quality software engineering and functional safety for this role.


  • Work directly with top OEM customers to set new autonomous vehicle AI/DNN safety performance criteria and establish DeepScale as the DNN safety thought leader.
  • Collaborate closely with our deep neural network development team, to create a functional safety program that demonstrates our commitment to the automotive industry and regulators to building trusted, safe DNN software products.
  • Build a safety team to research, deploy, assess, and revise DNN release performance criteria, meeting internal, industry, and regulatory QA/QC needs.