Senior Machine Learning Engineer, Ad Serving
Roku
| Company | Roku |
| Category | Engineering |
| Location | New York |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 8 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
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 highly scalable and highly available real-time advertising platform is crucial for supporting and growing Roku's advertising business. The mission of the Ad Engineering Team is to build this platform. The Ad Serving team designs, builds, deploys, and operates Roku’s Supply-Side, Ad Mediation, and Demand-Side platforms, which sit at the core of Roku’s ad monetization and are critical to the business. We are looking for a staff-level machine learning engineer with deep research and data science expertise to lead marketplace intelligence and demand optimization initiatives.
About the Role
This role will drive improvements in Roku Exchange efficiency by applying advanced data analytics and machine learning techniques to optimize pricing, allocation, and auction across the marketplace. For New York Only - The estimated annual salary for this position is between $195,000 - $510,000 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.
How will I use AI at Roku?
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.
What You'll Be Doing
Translate ambiguous business problems into clear hypotheses, measurable objectives, and actionable strategies
Develop advanced ML models and research-driven methodologies to drive product innovation and improve business outcomes
Design and run live experiments to prototype improvements and validate their effectiveness
Build production-grade ML systems that operate reliably in large-scale, low-latency ad serving environments
Partner with cross-functional stakeholders to define, plan, and drive the ML strategy for Ad Serving
Provide technical leadership and mentorship in machine learning, experimentation frameworks, and applied research best practices
We're Excited If You Have
10+ years of industry experience applying machine learning and data science to solve complex, mission-critical real-world problems
Deep expertise in statistics, machine learning, and optimization techniques
Perform as a staff+ technologist on complex, revenue-critical, large-scale distributed ML systems
Hands-on experience building and deploying ML models in production, includin
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