|Title: Deep Learning Video Scientist||Posted: June 17, 2015|
|Location: London, UK|
|Department: Research and Development|
Description: We are developing an exciting new key project identifying and tracking brands within variable length video data 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 the start.
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 and you'll be supported in this by a team of similar 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.
- 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
- PhD in Machine learning/Computer Vision
- BASH/CSH shell scripting
- 2+ years commercial experience
- 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 and the skills you could bring, to Dr Janet Bastiman (email@example.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.
We are not able to sponsor visas for relocation to the UK although remote working may be a possibility for an exceptional candidate.