Senior Machine Learning Engineer, Search
$361.3kRoku
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. About the Team Roku's Entertainment Assistant team is building the next generation of AI-powered discovery experiences across the platform through text, voice, and conversational interactions. The team owns the end-to-end discovery stack, including language understanding, GenAI-powered experiences, retrieval systems, ML-driven ranking and personalization, and whole-page optimization. We focus on delivering highly personalized and context-aware entertainment experiences while balancing user engagement, long-term retention, and monetization across Roku surfaces. Our systems leverage modern ML and GenAI techniques, including LLMs, reinforcement learning, multi-objective optimization, and agentic workflows, to help millions of users effortlessly discover content they love. About the Role We are looking for a Senior Machine Learning Tech Lead to drive ranking and personalization for Roku's next-generation entertainment assistant across the platform. This role sits at the intersection of Search, Recommendations, Conversational Discovery, and Monetization, with the goal of delivering highly engaging, personalized, and context-aware entertainment experiences. You will lead the development of large-scale ML systems that optimize for multiple objectives including user engagement, long-term retention, satisfaction, and monetization. The role requires strong technical leadership, product intuition, and the ability to balance user experience with business impact across diverse discovery surfaces. For California Only - The estimated annual salary for this position is between $361,300 - $510,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.
What You'll Do
We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
To learn more about Roku, our global footprint, and how we've grown, visit By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing View email address on click.appcast.io.
What You'll Do
- Lead the technical vision and roadmap for ranking, personalization, and recommendation systems powering Roku's entertainment assistant
- Develop and deploy state-of-the-art ML models using deep learning, transformers, LLMs, bandits, reinforcement learning, and causal inference techniques
- Build multi-objective optimization systems balancing engagement, retention, relevance, and monetization goals
- Drive innovation in conversational discovery, contextual recommendations, and personalized content experiences across the platform
- Design, run, and analyze online A/B experiments tied to key product and business KPIs
- Architect scalable ML systems, feature platforms, and data pipelines supporting rapid experimentation and long-term growth
- Mentor engineers and provide technical leadership across cross-functional initiatives involving engineering, product, UX, and analytics teams
- 8+ years of industry experience (or PhD with 5+ years) applying ML at scale in search, recommendation, ads, personalization, or related domains
- Strong expertise in ranking systems, recommendation systems, retrieval, personalization, and multi-objective optimization
- Experience building large-scale ML systems leveraging deep learning, sequence models, LLMs, reinforcement learning, or bandit frameworks
- Strong product intuition and experience optimizing user engagement, retention, and monetization simultaneously
- Proficiency in Python, Java, or Scala
- Experience with distributed systems and ML infrastructure such as Spark, Airflow, streaming systems, feature stores, and cloud platforms
- Strong technical leadership, system design, communication, and problem-solving skills
- MS or PhD in Computer Science, Statistics, or a related field
We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
To learn more about Roku, our global footprint, and how we've grown, visit By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing View email address on click.appcast.io.
Vacancy posted 3 days ago
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