Senior Software Engineer, Search & Recommendations Platform
RokuSan Jose, California$286k – $320kPosted 24 February 2026
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
Roku’s Search Recommendations (SR) Platform Engineering team is central to our mission of delivering outstanding streaming experiences to millions of people worldwide. We develop and maintain the core platform that powers search, personalization, and content discovery at scale across every Roku device and service.
We are a technically diverse and collaborative team that values ownership, transparency, and a culture of continuous improvement. We work closely with colleagues across platforms and infrastructure teams to deliver high-performance distributed systems and observability capabilities that enable real-time search, ranking, and recommendations.
Our work includes designing and optimizing online inference infrastructure, feature stores, and data pipelines — all seamlessly integrated with the broader platform ecosystem (Kubernetes, Istio, Envoy). We’re passionate about solving complex technical challenges that directly impact how users experience Roku.
About the Role
We are looking for a Senior Software Engineer with experience in building scalable, reliable systems to help evolve and extend the infrastructure behind our Search and Recommendations platform. In this role, you’ll be part of a cross-functional, globally distributed team dedicated to creating fast, cost-efficient solutions that deliver relevant and seamless user experiences.
You’ll contribute to the design, development, and operation of critical systems that power real-time search and personalized recommendations for millions of users. You’ll help shape the roadmap for our next-generation architecture, drive standardization and tooling efforts, and champion best practices in observability and resilience.
We are a fast-moving team with a strong engineering culture built on clear communication, thoughtful decision-making, and a shared commitment to delivering impactful solutions. Collaboration is fundamental to how we work — we invest as much in supporting our growth as we do in building exceptional systems.
For California Only - The estimated annual salary for this position is between $286,000 - $320,000 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.
What You’ll Be Doing
Design, build, and operate platform infrastructure powering real-time search and personalized recommendations
Work closely with machine learning engineers, data scientists, and infrastructure teams to scale our Machine Learning Platform
Shape the roadmap for our next-generation architecture, including improvements in cost efficiency, observability, and resilience
Drive tooling and standardization, working with the broader platform teams to identify and align on shared approaches
Design and implement multi-tenant systems and APIs that accelerate development, reduce coupling, and serve multiple teams across Roku
Take ownership of quality and system performance from design through deployment and operatio ... (truncated, view full listing at source)
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