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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. We seek an outstanding, creative, and passionate Machine Learning engineer to join Roku's Recommendation team. You will be responsible for building and owning the next generation of content recommendations and other algorithms/systems that will make the experience for our many millions of Roku users 100% personalized and unique.
Job Responsibility
Apply state of the art ML on recommendations using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimizations
Run online AB tests and analyze them against critical business KPIs
Collaborate with US engineering teams and cross-functional teams to translate business requirements into technical specifications
Nurture ML ecosystem to withstand scale, developer velocity and future business shifts
Help in training and mentoring new team members
Requirements
5+ years of experience applying Machine Learning to concrete problems at large scale
Strong CS fundamentals
Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models
Understanding of NLP approaches like W2V or Bert
Good understanding of system architecture
Experience in big data technologies – streaming architecture, data pipelines, etc.
Bachelors in Computer Science, Statistics, or related field
Nice to have
Build Recommender Systems for a living
Experience with Java, Scala, or Python
Work with big data systems – Spark, EMR, S3, AirFlow
Hold an MS or PhD in CS or related fields
AI literacy and curiosity
What we offer
Global access to mental health and financial wellness support and resources
Healthcare (medical, dental, and vision)
Life, accident, disability, commuter, and retirement options (401(k)/pension)