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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.    

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 You'll Be Doing

• 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
  

We're Excited If You Have

• 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

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