Senior Machine Learning Engineer, Content Platform

Roku•San Jose, CA

7d•$141,300 - $360,700•Hybrid

About The Position

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. About the Team Roku offers millions of options to our users: movies, shows, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning Engineer who can drive further innovation. About the Role The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best-in-class machine learning products. This includes integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement. This is a role for a hardened ML practitioner and a highly skilled organizational leader. You will be the architectural and operational bridge between deep AI research and fast-paced product delivery. If you know how to build a 3-year vision for content discovery and translate it into 2-week shipping cycles, this is your team.

Requirements

10+ years of total experience in software/ML engineering
MS or BS in Computer Science, Mathematics, or a related quantitative field
Deep theoretical and practical understanding of Machine Learning
You understand the business of streaming and how ML directly impacts the bottom line
You can explain complex models to a non-technical executive just as easily as you can debate architecture with a seasoned engineer
Proven track record of deploying large-scale ML models into production environments
Experience with modern ML stacks (e.g., LLMs, PyTorch, TensorFlow, Spark, and cloud-native MLOps tools)

Responsibilities

Define the roadmap for ML within the Content Platform
Provide high-level guidance on model architecture and MLOps infrastructure to ensure models are scalable and production-ready
Partner with Product, Engineering, and Content Strategy to align ML initiatives with business goals
Champion a culture of incremental delivery. Balance long-term R&D with the need to deliver measurable improvements to the production environment