Are you interested in large-scale machine learning and deep learning? Do you want to work with truly big data, huge multimedia content libraries, security videos from thousands of cameras, or the most advanced voice remote for the TV? Help millions of households discover video and music content on TV, Web, and Mobile?
If you have research experience in at least one or more of the following areas –Deep Learning, Recommendation Systems, NLP, Computer Vision, Information Retrieval, and Large-scale Machine Learning, we’re looking for you!
Comcast Labs Washington DC is currently looking to fill multiple graduate student intern positions for this summer (minimum of 12 weeks, May through September).
Potential projects will focus on (but are not limited to):
- Personalized recommendations and search for TV
- Multi-domain natural language understanding
- Knowledge generation, representation and inference for question answering systems using deep learning
- Deep learning based annotation, segmentation and recognition of broadcast videos and ads
- Object and activity recognition for home security
We are an innovative research group within Comcast’s Technology & Product organization that does groundbreaking research to support the development of novel Deep Learning and Machine learning based products for Comcast’s 22+ Million consumers.
Comcast is the largest provider of TV and Broadband Services in North America, the largest provider of TV search and discovery applications in North America, & the 6th largest provider of search on the web, and leading provider of smart home solutions.
The ideal applicant will be currently enrolled in a university PhD program and has 2+ years research experience in one of the relevant areas. Applicants should also have good programming and software development skills, and be comfortable working in an interdisciplinary, team-oriented, applied research environment.
Internships will be on-site in our Washington, DC office. We feature an informal, open atmosphere, and a location in downtown Washington convenient to several public transit lines and many of the city’s museums, monuments, and other attractions. The salary is competitive and commensurate with experience.
To apply, please send a CV or resume, along with a brief statement explaining why you are interested in the position, to Jan_Neumann(at)cable.comcast.com. We anticipate filling these positions latest by early 2016.
For more information please go to: http://dclabs.comcast.com/research/