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Senior Machine Learning Engineer - AdTech

RokuCambridge, United Kingdom연봉 협의정규직

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Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. About the Team Roku is the No. 1 TV streaming platform in the U.S., Canada, and Mexico with 70+ million active accounts. Roku pioneered streaming to the TV and continues to innovate and lead the industry. We believe Roku’s continued success relies on its investment in our machine learning recommendation engine. Roku enables our users to access millions of content titles including movies, episodes, news, sports, music, and channels from all around the world. About the Role We’re on a mission to build cutting-edge advertising technology that empowers businesses to run sustainable and highly profitable campaigns. The Ad Performance team owns server technologies, data, and cloud services aimed at improving the ad experience. We're looking for experienced engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using both general-purpose software and statistical languages.

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게시일 2026. 7. 5.
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