Senior Software Engineer, Machine Learning - Data Platforms
Confirmed live in the last 24 hours
Roku
Job Description
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
A reliable, privacy-safe, and scalable data foundation is critical to Roku’s rapidly growing advertising business. The Ad Data Activation organization builds the identity systems, device graph pipelines, audience platforms, insights tooling, and data collaboration capabilities that power targeting, measurement, and reporting across Roku Ads.
We are hiring a Senior Machine Learning Engineer to help drive intelligence across these systems. You will work at the intersection of large-scale data platforms, applied machine learning, and generative AI — building capabilities that make Roku's advertising data more actionable for internal teams and advertisers. This includes building core generative AI platform features for Roku Advertising, while also applying traditional ML techniques to improve accuracy, automation, and decisioning across the ecosystem. If you enjoy working across data, ML, and new Gen-AI patterns — and want to shape how intelligence shows up inside Roku Ads — this role is for you.
About the role
In this role, you will design, build, and productionize intelligent capabilities that combine agentic Gen-AI systems with conventional ML pipelines across identity resolution, audience modeling, attribution, and optimization workflows. You will work with massive datasets, develop pipelines that transform raw signals into actionable features, and partner closely with product, data science, and platform teams.
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