| | Title: Lead Machine Learning / Computer Vision Engineer | Posted: July 10, 2015 | | Company/Institution: Stanford University | | Location: Stanford CA | | Department: Computer Science / Pediatrics |
Description: We are looking for a driven machine learning and computer vision engineer to co-lead our core technology team on the Autism Glass Project.
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
Desired:
- 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 Caffe
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Application Instructions: Contact nhaber at stanfordedu |
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