Roku provides the simplest way to stream entertainment to your TV. On your terms. With thousands of available channels to choose from. Backed by Menlo.
About the role
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.
What they're looking for
- 5+ years of experience building software solutions to concrete problems
- Strong CS fundamentals. Should be able to write an algorithm with ease
- You are fluent with one of the high-level programming languages like Java, Scala, Kotlin, or Python
- We’d love to see that you’ve worked with big data systems (Spark, Kafka, Flink, S3, AirFlow)
- Familiar with model ML frameworks and tools: Ray, PyTorch, HuggingFace, AWS Sagemaker
- AI literacy and curiosity. You have either tried Gen AI in your previous work or outside of work, or are curious about Gen AI and have explored it
More about this role
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.
The Recommendations team drives personalized experiences across our platform by leveraging state-of-the-art machine learning. Our mission is to deliver meaningful, context-aware recommendations that adapt to each user's preferences in real time. We believe that true innovation in personalization requires more than great models—it depends on a robust, flexible ML platform built for experimentation and scale. To that end, we design and build the underlying ML...
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