Title: Lead Machine Learning / Computer Vision Engineer
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
Application Instructions: Contact nhaber at stanford [make the dot] edu
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
Application Instructions: Contact nhaber at stanford [make the dot] edu