Machine Learning / Computer Vision Engineer

We are looking for a driven machine learning and computer vision engineer to work with our core technology team on the Autism Glass project, a multidisciplinary project in the Stanford School of Medicine. Our team has developed a system using machine learning and artificial intelligence to automate facial expression recognition that runs on wearable glasses and delivers real-time social cues to children with Autism. You can see the system in action and find some recent background on the projects in KQED, SF Chronicle, Scientific American, and CBS.

As a CV/ML engineer, you should have a strong background in applied mathematics, optimization, machine learning, and software development. We are working on research problems on a product development timeline, so you should be enough of a scientist to be able to understand and implement your average ICCV paper, and enough of a hacker to be able to immerse yourself in challenging tasks without much guidance or background and write production-ready code. Ideal candidates for this position have a PhD or MS in a field related to artificial intelligence as well as publications at conferences such as ICCV or NIPS.

Required experience:

  • Linear Algebra
  • Machine Learning
  • Programming experience on a large-scale project in C/C++
  • Computer Vision and OpenCV
  • Comfortable in a Unix environment with common developer tools


  • Knowledge of Objective-C, iOS, and Android development
  • GPU Programming experience
  • At least one scripting language and a basic understanding of processing large datasets
  • Previous work in face tracking, face recognition, or expression recognition
  • Image processing background
  • Deep learning experience and familiarity with Theano, Caffe, or Tensorflow

Please contact Nick Haber at about this position.