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Salary
$361k – $510k per year
Location
Hybrid (San Jose, United States)
Seniority
Senior · 8+ years exp
Visa
H-1B filings in 12 months: 63 · for this role: 43 · green card filings: 7
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on May 21, 2026.

Overview
Company
Impact
Profile match
Roku provides the simplest way to stream entertainment to your TV. On your terms. With thousands of available channels to choose from.
Backed by Menlo Ventures

Join Roku's Entertainment Assistant team as a Senior Machine Learning Engineer. In this role, you will lead the development of large-scale ML systems that optimize for multiple objectives, including user engagement, long-term retention, satisfaction, and monetization. You will drive innovation in conversational discovery, contextual recommendations, and personalized content experiences across the platform. The position requires strong technical leadership, product intuition, and the ability to balance user experience with business impact.

Missions

  • Lead the development and deployment of large-scale machine learning models for ranking and personalization in Roku's entertainment assistant.
  • Drive innovation in conversational discovery, contextual recommendations, and personalized content experiences across the platform.
  • Architect scalable machine learning systems, feature platforms, and data pipelines supporting rapid experimentation and long-term growth.

Profil recherché

- Strong technical leadership, system design, communication, and problem-solving skills

- 8+ years of industry experience (or PhD with 5+ years) applying ML at scale in search, recommendation, ads, personalization, or related domains

- Strong product intuition and experience optimizing user engagement, retention, and monetization simultaneously

- Experience with distributed systems and ML infrastructure such as Spark, Airflow, streaming systems, feature stores, and cloud platforms

- Experience building large-scale ML systems leveraging deep learning, sequence models, LLMs, reinforcement learning, or bandit frameworks

- Strong expertise in ranking systems, recommendation systems, retrieval, personalization, and multi-objective optimization

- Proficiency in Python, Java, or Scala

- MS or PhD in Computer Science, Statistics, or a related field

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