PamiTC Job Board - Posting Details

Title: Deep Learning Scientist - still images and videoPosted: August 11, 2015
Company/Institution: SnapRapid
Location: London, UK

Description: We are developing an exciting new project identifying and tracking brands within variable length video and still images from multiple sources using deep learning for identification of symbols, text and objects. If you have experience in this area then this is a fantastic opportunity to become an integral part of (or lead) this project from early in. We're looking for passionate and talented individuals with an entrepreneurial approach to work, constantly looking for new ways of doing things to get fast results. You'll be surrounded and supported in by a team of like minded individuals. You will be part of the core Research and Development team within SnapRapid and will be key in development of the visual processing and deep learning application. We work in a fast paced, agile environment, where we collaborate and peer review ideas alongside traditional code and test cycles. We encourage presentation of cleared work through conferences and papers and continual learning within the team. Requirements • Experience with video analysis using deep learning is essential • M.S Degree or higher in computer science or related fields • High proficiency in Python • Ability to turn academic ideas into practical code • Strong working knowledge of software architecture and data structure • Effective oral and written communication skills in English Desirable skills: • PhD in Machine learning/Computer Vision • BASH/CSH shell scripting • Experience of multi-core architectures • Strong ability in other programming languages (JS,PHP, C,.Net etc)

Application Instructions: Please send your CV, along with a cover letter indicating your suitability for the role, availability and the skills you could bring, to russell@snaprapid.com. Please note, due to the high number of applications received in response to previous posts we may not be able to reply individually to all applicants.