Senior Software Engineer, Machine Learning

What does the team work on?

Roku Search team directly contributes to Roku's mission by helping connect users to the content they like and enabling content publishers to build and monetize large audiences. Our team builds state-of-the-art machine learning algorithms to optimize search relevance and highly scalable, reliable & low latency search platform infrastructure to power a delightful search experience.

What is the role?

Roku's footprint has more than quadrupled in the past five years, and user expectations have leaped just as fast-think LLM-based query understanding, vector-DB retrieval, on-device models, and multimodal search (voice, text, image). We're now rebuilding our relevance stack for the next decade, blending classic IR with generative-AI techniques. You will be a technical leader spearheading that transformation. You will apply state-of-the-art ML on search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimizations to make our users more delighted and engaged on the platform. You will collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications, and provide technical leadership to drive the technical and ML roadmap for search ranking and monetization. This is a high-impact role where you will nurture our ML ecosystem to withstand scale, developer velocity, and future business shifts.

How will I use AI at Roku?

At Roku, we don't just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability. We're looking for curious, adaptable builders who can show how they've used AI or automation to move faster, raise the bar, and scale their impact.

We value your AI skills if you have built fluency across the agentic engineering toolchain - coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you.

What are the responsibilities of the role?

• Apply state-of-the-art ML on search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimizations to make our users more delighted and engaged on the platform
• Run online A/B tests and analyze them against the critical business KPIs
• Collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications
• Nurture our ML ecosystem to make it withstand scale, developer velocity, and future business shifts
• Provide technical leadership to drive technical and ML roadmap for search ranking and monetization
• Help recruit new engineers, interview, train, and mentor new team members

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

• 6+ years of experience (or PhD with 5 years of experience) applying Machine Learning to concrete problems at large-scale in domains like recommendation, search, or ads
• Strong computer science fundamentals with the ability to convert ideas to code with ease
• Good understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models; familiarity with modern NLP stack and multi-modal representation learning is a plus
• Experience working with big data systems (Spark, S3, and Airflow) and proficiency in Java, Scala, or Python
• Good understanding of system architecture
• Experience in big data technologies and streaming architecture, data pipelines, etc
• Master's degree in Computer Science, Statistics, or related field; PhD in Computer Science or related fields preferred
• You have built fluency across the agentic engineering toolchain - coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you