Senior Software Engineer, Machine Learning; Level

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.

Roku pioneered TV streaming and continues to innovate and lead the industry. The Roku Channel has us well-positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them.

Within Advertising Engineering, the Mar Tech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience to the right customer at the right time on the right marketing channel. The team is focused on turning data, experimentation, and intelligent decisioning into production systems that improve marketing effectiveness at scale.

Our mission is to build cutting‑edge advertising technology and marketing products to support and grow a sustainable advertising business. The team owns server technologies, data platforms, and cloud services that power advertising and marketing use cases.

We are recruiting a Senior Machine Learning Engineer to build and enhance intelligent systems that help the marketing team harness the power of data.

The Mar Tech team at Roku is looking for a seasoned Senior Machine Learning Engineer with a strong background in machine learning and production systems. This role sits in a team working on high-impact problems across marketing and advertising, where machine learning is being applied to improve customer decisioning, creative and campaign performance, and the systems that support experimentation and optimisation.

Examples of such problems include creative personalisation for customers, improving ad relevance and targeting, inferring demographics, yield optimisation, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, recommendations, reinforcement learning, optimisation, probability theory, and machine learning, using code for statistical analysis and tool building, using both general-purpose software and statistical languages.

The ideal candidate will have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond quickly to changing business needs.

This role requires hybrid working from the Roku Manchester office.

• Data Analysis / Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models.
• Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system performance, quality and accuracy.
• Near Real-Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads.
• ML Infrastructure: Help build a first-class machine learning platform from the ground up which helps manage the entire model lifecycle: feature engineering, model training/evaluation, versioning,…