Senior Machine Learning Engineer, Data Insights

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 The Data Insights team plays a critical role in Roku's Advertising organisation, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal teams. We work closely with Product Managers, Data Science, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions. We are investing in machine learning and generative AI to transform how advertisers measure, understand, and optimise their campaigns — from predictive measurement models to agentic, natural-language analytics experiences. About the Role We are seeking a highly skilled Senior Machine Learning Engineer to design, build, and productionise ML and generative-AI systems that power Roku's advertising measurement and insights products. This role bridges applied machine learning and production engineering: you will own models end-to-end, from framing the problem and engineering features through deployment, monitoring, and iteration at scale. You will work with large-scale advertising datasets and a modern data and ML stack — including Apache Spark, Apache Airflow, Trino, Druid, and StarRocks — and partner closely with software engineers, data scientists, and product managers to turn models into reliable, high-impact products. You will also help shape our generative-AI roadmap, building agentic experiences such as reporting and insights agents and a semantic layer for trustworthy natural-language analytics. The ideal candidate is a proactive, self-motivated professional with a strong track record of applying ML to real business problems at scale and a dedication to delivering measurable outcomes. What You'll Be Doing • Develop scalable, effective ML models and data pipelines to power measurement, audience insights, campaign performance intelligence, and advertiser-facing analytics • Design and run experiments, measure impact, and translate results into product decisions and customer outcomes • Build and productionise agentic, generative-AI features — including reporting and insights agents, campaign-monitoring agents with human-in-the-loop controls, and a semantic layer for reliable, natural-language analytics • Improve automation, reliability, and scalability across model training, feature engineering, deployment, and monitoring • Partner with software and ML engineers to deliver end-to-end solutions from data ingestion through downstream products and APIs • Work with senior stakeholders to shape ML and Gen-AI strategy for advertising measurement — identifying the right problems for AI, ensuring safety and quality, and driving advertiser productivity • Provide technical guidance and mentorship to other engineers, promoting best practices in ML and production engineering • Lead data-driven experimentation and advanced measurement — including incrementality and lift studies that quantify the value of advertising on Roku and its incremental impact across an advertiser's broader media mix We're Excited If You Have • 5+ years of experience applying ML or data science to real business problems at scale</