Parallel & Embedded Tools Computing Engineer (Tools/Infra) at DeepScale

DeepScale

Parallel & Embedded Tools Computing Engineer (Tools/Infra)

Full-Time in Mountain View, CA - Mid Level - Engineering

DeepScale, Inc. is a fast growing start-up in the Advanced Driving space, providing perceptual systems for Advanced Driver Assist Systems and Autonomous Vehicles. 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 prior 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.

Job Description

Create and maintain development tools and flows for deploying deep-learning based systems targeting modern embedded and parallel platforms.

Responsibilities

  • Bringup-of and doing-development-on various embedded linux platforms suitable for deploying deep learning applications, ranging from ~10W ARM CPU based SBCs to ~200+W NVIDIA Drive PX modules.
  • “Take this piece of specialized hardware and make it work.” -- Forrest Iandola, DeepScale CEO

Important Qualifications

  • Ability to create and use toolchains for targeting a variety embedded platforms.
  • Basic familiarity with Yocto, Debian, Android, and/or Linaro.
  • Experience cross-building complex C++ packages for embedded linux platforms (including android).
  • Ability to create and deploy (to development clusters) systems that perform automated, replicable builds of software stacks for deploying deep learning, including both open-source components as well as DeepScale internal models and tools.
  • Significant experience with cross-compiling C/C++ software to embedded linux platforms using Debian/Ubuntu and/or Linaro cross-toolchains.
  • Experience with use and/or administration of compute/development/NN-training/GPU clusters.
  • Experience with HPC/cluster storage, network, and/or administrative infrastructure.

Nice-to-have Qualifications

  • Significant experience with cross-compiling C/C++ software to Android using the Android NDK.

Education/Experience Required

  • Minimum BS
  • 4 years’ work experience in a related field