Nielsen Media would not function without our Technology teams! We are catalysts for delivery quality, on-time, reliable measurements to clients, and we are cultivators, growing our employees through education, skill building and experiences. Around the globe, our Technology teams are relentless in our pursuit of superior analytics, technology, process and support.
The Machine Learning Engineer will work on new technology and research projects within the content recognition and classification area of Nielsen. You will be working to identify and/or classify content from both audio and video. In order to make these technologies, you should have a good theoretical background and practical experience with machine learning systems. Theoretical knowledge about audio or video is required, and you should be capable of performing signal processing on either audio or video data. We expect you to be well versed in engineering best practices and software design concepts, and to be able to document and explain your work. You will coordinate your 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 the next content recognition or classification product. As time allows, you will advise and lead other engineering colleagues and student interns. You could also initiate or participate in the publication of scientific papers, and represent Nielsen at scientific conferences.
- Bachelor’s degree in Computer Science and/or Electrical Engineering and at least 3 years of practical experience in multimedia signal processing and programming. Masters or PhD in Computer Science, Electrical Engineering, or a related field is preferred.
- Solid fundamentals (practical and theoretical) in machine learning and digital signal processing of either audio or video.
- 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 debugging techniques and applications development.
- Knowledge of audio or video fingerprinting
- Experience handling large amounts of data and familiarity with databases. Bash and 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 publications and technical papers.
By connecting clients to audiences, we fuel the media industry with the most accurate understanding of what people listen to and watch. To discover what audiences love, we measure across all channels and platforms—from podcasts to streaming TV to social media. And when companies and advertisers are truly connected to their audiences, they can see the most important opportunities and accelerate growth.
Do you want to move the industry forward with Nielsen? Our people are the driving force. Your thoughts, ideas and expertise can propel us forward. Whether you have fresh thinking around maximizing a new technology or you see a gap in the market, we are here to listen and take action. Our team is made strong by a diversity of thoughts, experiences, skills, and backgrounds. You’ll enjoy working with smart, fun, curious colleagues, who are passionate about their work. Come be part of a team that motivates you to do your best work!
Nielsen is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class.
Job Type: Regular
Primary Location: Oldsmar, Florida
Secondary Locations: FL - Tampa - Oldsmar, , ,