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The Machine Learning Engineer will work on new technology and research projectswithin the content recognition and classification area of Nielsen. You will be working toidentify and/or classify content from both audio and video. In order to make thesetechnologies, you should have a good theoretical background and practical experiencewith machine learning systems. Theoretical knowledge about audio or video is required,and you should be capable of performing signal processing on either audio or videodata. We expect you to be well versed in engineering best practices and softwaredesign concepts, and to be able to document and explain your work. You will coordinateyour work with the tasks of colleagues from your own team and other Nielsen teams.You will interact with Nielsen customers and partners as required while developing thenext content recognition or classification product. As time allows, you will advise andlead other engineering colleagues and student interns. You could also initiate orparticipate in the publication of scientific papers, and represent Nielsen at scientificConferences.
Requirement
• Bachelor’s degree in Computer Science and/or Electrical Engineering and atleast 5+ years of practical experience in multimedia signal processing andprogramming. Masters or PhD in Computer Science, Electrical Engineering, or arelated field is preferred.• Solid fundamentals (practical and theoretical) in machine learning and digitalsignal processing of either audio or video. Must be proficient in multiple modeling techniques including neural networks.• Experience with accelerated machine learning tools such as Tensorflow, Keras,PyTorch, etc.• Experience developing end to end project workflow in machine learning systems.This includes literature review, data collection, building ML system infrastructure,evaluation systems, and production/integration into a final service.• Good programming skills in Python and C/C++. Good knowledge of debuggingtechniques and applications development.• Knowledge of audio or video fingerprinting• Experience handling large amounts of data and familiarity with databases. Bashand shell scripting experience.• Very good knowledge of Linux/Unix platforms and Windows or Mac OS.• Knowledge about visual perception, and/or audio and music theory.• Experience with cloud services such as AWS or Google Cloud• Quickly understand and properly judge the applicability of scientific publicationsand technical papers.
