Senior Machine Learning Engineer

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.

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.

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.

For New York Only - The estimated annual salary for this position is between $229,500 - $360,000 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.

At Roku, we don't just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability. We’re looking for curious, adaptable builders who can show how they’ve used AI or automation to move faster, raise the bar, and scale their impact.

We value your AI skills if you have built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you.

• Design, build, and maintain scalable platform services: feature store, real-time inference services, vector DBs, etc., that serve millions of transactions per second
• Run and monitor online AB tests via robust platform services, analyzing platform metrics and business KPIs to optimize recommendation system performance
• Collaborate closely with US-based engineering and cross-functional teams to translate business requirements into modular platform components and APIs
• Enhance and evolve the ML platform ecosystem to support high developer velocity, system scalability, and adaptability to future business needs
• Contribute to onboarding, training, and mentoring new team members on emerging platform engineering best practices and technologies

• 5+ years of experience building software solutions to concrete problems
• Strong CS fundamentals. Should be able to write an algorithm with ease
• You are…