Senior Machine Learning Engineer, Search Assistant
Roku · San Jose, CA · 224 - Search & Recommendations
About this role
Roku is hiring a senior-level Machine Learning Engineer based in San Jose, CA. The posting calls out experience with Python, Java, Scala, Spark. Compensation is listed at $361,300–$510,000 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Jose, CA
- Department
- 224 - Search & Recommendations
More roles at Roku
Job description
from Roku careersTeamwork 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 Entertainment Assistant team is building the next generation of AI-powered discovery experiences across the platform through text, voice, and conversational interactions. The team owns the end-to-end discovery stack, including language understanding, GenAI-powered experiences, retrieval systems, ML-driven ranking and personalization, and whole-page optimization.
We focus on delivering highly personalized and context-aware entertainment experiences while balancing user engagement, long-term retention, and monetization across Roku surfaces. Our systems leverage modern ML and GenAI techniques, including LLMs, reinforcement learning, multi-objective optimization, and agentic workflows, to help millions of users effortlessly discover content they love.