Senior Machine Learning Engineer - Content Platform

The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best-in-class machine learning products. This includes integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement. Communication and presentation skills are essential as you'll collaborate across teams. The role requires high technical aptitude, problem-solving abilities, motivation, and exceptional attention to detail. We're always in build mode because we're a company of data-focused builders. Every day, you'll look at what exists and find ways to make it better.
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.
Responsibilities:
Building and owning the next generation of content knowledge platforms and other algorithms/systems that create high-quality and unique experiences for millions of Roku users.
Designing and implementing advanced Machine Learning models for entity matching, data deduplication, and Generative AI tasks such as content summarisation, deduplication, and metadata quality.
Developing and maintaining Deep Learning models for data quality checks, visual similarity scoring, and content tagging.
Implementing KPI measurement frameworks to evaluate the quality and performance of delivered models, including those utilising Generative AI.
Creating products that provide exceptional user experiences while meeting performance, security, quality, and stability requirements.
Requirements:
7+ years of experience applying Machine Learning and GenAI to solve concrete problems at large scale.
Strong CS fundamentals, with the ability to design algorithms for real-world challenges.
Expertise in machine learning fundamentals, including deep generative models (GANs, VAEs), transformers, tree-based methods, and sequence-based models.
Proven familiarity with NLP approaches like BERT, GPT, or related architectures, as well as Vision-based approaches like ResNet, EfficientNet, or CLIP.
Experience in big data systems (e. g., Spark, EMR, Kafka, S3 Flink, Airflow) and programming (Java, Scala, or Python).
A track record of building in-production Machine Learning systems, including deploying Generative AI and Vision Model-based pipelines.
Knowledge of system architecture and experience with big data technologies (e. g., streaming architectures, scalable data pipelines).
An understanding of state-of-the-art Vision Models for tasks such as image classification, object detection, and multimodal learning.
MS in Computer Science, Statistics, or a related field is required; a PhD in CS or related fields is preferred.

Experience
5-9 yrs