Machine Learning Engineer 🔥
Are you ready to revolutionize entertainment? If you want to learn how people discover video and media they like online then Nielsen and Gracenote is a place for you. Gracenote, a Nielsen Company is the leading provider of entertainment metadata and media recognition technology that powers discovery features and discover the music, TV shows, movies and sports they love across the world’s most popular entertainment platforms and devices. We deliver mission critical data to help our clients grow their business with our extensive and quality data verified by real consumers.
We are looking for a Machine Learning Engineer to work with the Video Machine Learning team to solve a number of cutting edge challenges in media and entertainment. Our products enable next-gen entertainment services, facilitating search, content recommendations, personalization, faceted navigation, rich media and more. Our analytics solutions provide high quality insights into audience behaviors and content performance to drive effective decision making for our global customers.
You will:
- Analyze, design, develop, test, document and support highly advanced data science and machine learning projects.
- Develop machine learning algorithms related to classification, clustering, regression and more.
- Develop computer vision algorithms using features such as brightness, color, motion and blur.
- Write Python code for machine learning algorithms using pandas, scikit-learn, Py Torch or Tensor Flow.
- Set up infrastructure on AWS to deploy code in a production environment.
- Review peers’ code and machine learning techniques.
- Write up technical summary documents of the machine learning problem statement, techniques applied and challenges encountered.
Requirements:
- At least one year of full time industry experience using machine learning to build maintainable solutions in a production environment using Python or a similar programming language.
- Experience with using machine learning concepts including common families of models, feature engineering and selection, cross-validation and parameter tuning, common computer vision and deep learning algorithms and frameworks.
- Experience with machine learning toolboxes such as scikit-learn and PyTorch.
- Excellent communication skills and the ability to work well within and across teams.
- Bachelor's or graduate degree in a quantitative field (e.g. CS, math, physics, statistics, engineering).
Bonus:
- Experience with tools for distributed computing (e.g. Spark, Elasticsearch)
- Working knowledge of SQL
- Familiarity with cloud infrastructure such as AWS
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: Emeryville, California Secondary Locations: , , , Travel: No
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