Machine Learning Engineer, Ads at King
San Francisco, California, United States
🇺🇸 (Posted Jun 12 2018)
About the company
King is a leading interactive entertainment company for the mobile world, with people all around the world playing one or more of our games. We have developed more than 200 fun titles, and offer games that are enjoyed all around the world. King is an independent unit of Activision Blizzard Inc. (Nasdaq: ATVI), which acquired King in February 2016.
King (a part of Activision-Blizzard) is building a new team to introduce innovative, impactful, and rewarding advertising experiences to our 300+ million audience of highly-engaged players and to create powerful marketing solutions embraced by the world’s biggest marketers.
King is seeking a Machine Learning Engineer in our Ads Engineering team, empowering cutting edge mobile advertising technologies to create the next generation of our Ads Platform.
Your role within our Kingdom
Aggregate huge amount of data and information from large numbers of sources to discover patterns and features necessary to build machine learning models for prediction and forecasting.
Design and implement end-to-end solutions using Machine Learning, Optimization, and other advanced computer science technologies, and own live deployments to drive advertising conversion.
Improve the run-time of existing algorithms.
Develop and maintain necessary infrastructure to run and maintain the algorithms.
Develop a feedback system to improve the selection of features for the algorithms.
Skills & requirements
PhD or MS in computer science, engineering or related field.
4-8 years of experience as machine learning engineer/data scientist.
You have expertise in one or more object-oriented languages, including Python, Go, Java, or C++, and an eagerness to learn more.
Experience with both machine learning and building scalable production services.
Experience with distributed storage and database systems, including SQL or NoSQL, MySQL, or Cassandra.
Experience in stream processing—Storm, Spark, Flink etc.— and graph processing technologies.
Experience using machine learning libraries or platforms, including Tensorflow, Caffe, Theanos, Scikit-Learn,or ML Lib for production or commercial products.
A strong desire to learn the details of advance machine learning algorithms.
Ability to communicate effectively between Product managers, business teams, data analysts and production engineers, both in code and conversation.
Ability to solve complex business problems and apply machine learning to optimize critical business metrics.
Strong adherence to metrics driven development, with a disciplined and analytical approach to product development.
Instructions how to apply
see the website
[ job website
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