Senior Machine Learning Engineer, Data Insights

What does the team work on?

The Data Insights team plays a critical role in Roku's Advertising organisation, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal teams.

We work closely with Product Managers, Data Science, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.

We are investing in machine learning and generative AI to transform how advertisers measure, understand, and optimise their campaigns — from predictive measurement models to agentic, natural-language analytics experiences.

What is the role?

We are seeking a highly skilled Senior Machine Learning Engineer to design, build, and productionise ML and generative-AI systems that power Roku's advertising measurement and insights products. This role bridges applied machine learning and production engineering: you will own models end-to-end, from framing the problem and engineering features through deployment, monitoring, and iteration at scale. You will work with large-scale advertising datasets and a modern data and ML stack — including Apache Spark, Apache Airflow, Trino, Druid, and StarRocks — and partner closely with software engineers, data scientists, and product managers to turn models into reliable, high-impact products. You will also help shape our generative-AI roadmap, building agentic experiences such as reporting and insights agents and a semantic layer for trustworthy natural-language analytics. The ideal candidate is a proactive, self-motivated professional with a strong track record of applying ML to real business problems at scale and a dedication to delivering measurable outcomes.

How will I use AI at Roku?

At Roku, AI agents do most of the keystroke-level coding. Engineers act as the technical leads for those agents — setting context, planning work, verifying outputs, and recovering when the agent goes off course. If you are excited about working this way, we want to talk to you.

At Roku, we're embracing AI as a powerful tool to amplify human creativity, accelerate innovation, and deliver better results for our customers. Across teams, we're exploring how AI can enhance our work — and we're only looking for people who are curious, adaptable, and excited to grow alongside these technologies.

What are the responsibilities of the role?

• Develop scalable, effective ML models and data pipelines to power measurement, audience insights, campaign performance intelligence, and advertiser-facing analytics
• Design and run experiments, measure impact, and translate results into product decisions and customer outcomes
• Build and productionise agentic, generative-AI features — including reporting and insights agents, campaign-monitoring agents with human-in-the-loop controls, and a semantic layer for reliable, natural-language analytics
• Improve automation, reliability, and scalability across model training, feature engineering, deployment, and monitoring
• Partner with software and ML engineers to deliver end-to-end solutions from data ingestion through downstream products and APIs
• Work with senior stakeholders to shape ML and Gen-AI strategy for advertising measurement — identifying the right problems for AI, ensuring safety and quality, and driving advertiser productivity
• Provide technical guidance and mentorship to other engineers, promoting best practices in ML and production engineering
• Lead data-driven experimentation and advanced measurement — including incrementality and lift studies that quantify the value of advertising on Roku and its incremental impact across an advertiser's broader media mix

What experience would help someone be successful in this role at Roku?

• 5+ years of experience applying ML or data science to real business problems at scale
• Master's degree (or higher) and 4+ years of experience in Computer Science, Computer Engineering, Machine Learning, or a related field (or equivalent experience)
• Strong computer science fundamentals and the ability to design efficient algorithms and production systems
• Experience with ML approaches used in large-scale data problems (e.g., regression, classification, tree-based methods, embeddings, sequence models, or NLP)
• Strong intuition for defining KPIs, objective functions, and evaluation frameworks for ML-driven systems
• Proficiency in one or more programming languages such as Python, Scala/Java, or C/C++
• Experience with large-scale data platforms (Spark, Trino/Presto, feature stores, data lakes, etc.)
• Experience building or integrating with LLM/Gen-AI pipelines (prompting, evaluation, retrieval, safety)
• Experience in AdTech, advertising data platforms, or campaign measurement
• Familiarity with analytics engines such as Druid, Trino, or StarRocks and visualisation tools like Looker
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