Senior Machine Learning Engineer, Platform

Roku
San Jose, California$230k – $367kPosted 5 March 2026

Job Description

<div class="content-intro"><h2 style="font-family: GothamBold,Helvetica,Arial,sans-serif; color: #662d91;">Teamwork makes the stream work.</h2> <p> </p> <h3 style="font-family: GothamBold,Helvetica,Arial,sans-serif;"><strong>Roku is changing how the world watches TV</strong></h3> <p>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.</p> <p>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.</p> <p> </p></div><h3><strong>About the Team</strong></h3> <p>The Recommendations team drives personalized experiences across our platform by leveraging state-of-the-art machine learning. Our mission is to deliver meaningful, context-aware recommendations that adapt to each user's preferences in real time. We believe that true innovation in personalization requires more than great models—it depends on a robust, flexible ML platform built for experimentation and scale. To that end, we design and build the underlying ML infrastructure, ensuring our systems remain fast, reliable, and at the forefront of technology. Our work blends innovation, engineering excellence, and a deep commitment to understanding our users, shaping how they discover and engage with content every day.</p> <h3><br><strong>About the Role</strong></h3> <p>We seek an outstanding, creative, and passionate Machine Learning Platform Engineer to join Roku's Recommendation team. In this role, you will design, build, and scale robust distributed systems that power the next generation of personalized content recommendations for millions of Roku users. You will focus on developing end-to-end machine learning platforms and infrastructure, ensuring seamless deployment, monitoring, and optimization of algorithms and operational workflows that deliver unique experiences at scale.<br><br>For California Only - The estimated annual salary for this position is between $229,500 - $367,100 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.<br> </p> <h3><strong>What You'll Be Doing</strong></h3> <ul> <li>Design, build, and maintain scalable platform services: feature store, real-time inference services, vector DBs etc., that serve millions of transactions per second</li> <li>Run and monitor online AB tests via robust platform services, analyzing platform metrics and business KPIs to optimize recommendation system performance</li> <li>Collaborate closely with US-based engineering and cross-functional teams to translate business requirements into modular platform components and APIs</li> <li>Enhance and evolve the ML platform ecosystem to support high developer velocity, system scalability, and adaptability to future business needs</li> <li>Contribute to onboarding, training, and mentoring new team members on emerging platform engineering best practices and technologies<br><br></li> </ul> <h3><strong>We’re Excited If You Have</strong></h3> <ul> <li>5+ years of experience building software solutions to concrete problems</li> <li>Strong CS fundamentals. Should be able to write an algorithm with ease</li> <li>You are fluent with one of high-level programming languages like Java, Scala, Kotlin or Python</li> <li>We ... (truncated, view full listing at source)
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