Are you interested in building intelligent applications that impact millions of people on a daily basis? Do you have experience in Deep Learning and its applications in at least one or more of the following areas –NLP, Computer Vision, Recommendation Systems, or Data Science? Do you want to conduct industry-leading research to help millions of households discover and enjoy video and music content on their TV, PC, and Mobile devices and be delighted by smart internet and home experiences? Do you want to help us build the interfaces that will allow our customers to interact with our products using natural speech?
Comcast Labs Washington DC is currently looking to grow their machine learning research group with senior and junior researchers that focus on using Deep Learning for NLP, Video Analytics, Personalized Search and Recommendations, and other Artificial Intelligence applications.
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 candidate will have experience working as a technical lead or researcher in an industrial, government, or academic lab setting on deep learning projects and applicants with a Ph.D. are preferred.
Applicants should have good programming and software development skills, and be comfortable working in an interdisciplinary, team-oriented, applied research environment. Familiarity with Python, Java or Scala, C++ and knowledge of deep learning frameworks such as TensorFlow, MXNet, Caffe, Torch, Keras, etc. is preferred.
The position will be located 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@cable.comcast.com.
For more information about our group please go to: http://dclabs.comcast.com/research
– Develops algorithmic solution and technical requirements of custom designs for future products and applications.
– Leads research projects in one or more of the following areas: Deep Learning, Recommendation Systems, Information Retrieval, and Large-scale Machine Learning.
– Works with other Technical Leads, Product Managers and Business Partners to lead development of prototypes that demonstrate Research work, help with Product Discovery and integrate research output into engineering code base.
– Works with various team members both within and outside Research. Ensures timely progress of work. Conducts Research in an incremental manner thereby enabling faster integration of technology into products. Able to evaluate prototype systems, write technical papers, and help with technology transfer.
– Keeps track of developments in field both in academia and in industry. Attending relevant conferences and publishing research results is encouraged.
Education Level: Master’s Degree or Equivalent; Ph.D. strongly preferred.
Field of Study: Computer Science, Data Science or Applied Math with experience in one or more of the following areas: Deep Learning, Recommendation Systems, Information Retrieval, Large Scale Machine Learning, Data Science, NLP, or Computer Vision.
Years of Experience: Generally requires 7-10 years related experience after Bachelors, 5-8 years after Master’s, or 2-3 years after Ph.D for lead positions, and 5-8 years related experience after Bachelors, 2-3 years after Master’s, or a recent Ph. for junior research positions.
Compliance: Comcast is an EEO/AA/Drug Free Workplace.
Disclaimer: The above information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.