ML Engineer

Roku · Bengaluru

  • Experience6–9 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelsenior
  • Posted2 Sept 2026
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About Roku

Roku is hiring in Bengaluru in media advertising. This role looks for around 6+ years of experience.

Skills

  • Machine Learning
  • Deep Learning
  • Recommendation Systems
  • Natural Language Processing
  • Data Science
  • Regression
  • Classification
  • Neural Networks
  • Sequence Models
  • Causal Inference
  • A/B Testing
  • System Architecture
  • Streaming Architecture
  • Data Pipelines
  • Computer Science
  • Statistics

The role

A machine learning engineer at a personalized media platform applies machine learning to recommendation systems, deep learning, and natural language processing, and evaluates algorithms through online experiments and big-data pipelines. The role also develops scalable system architecture and recommendation models using Java, Scala, or Python.

Full job description

We seek an outstanding, creative, and passionate Machine Learning Engineer to join Roku's Recommendation team. You will be responsible for building and owning the next generation of content recommendations and other algorithms/systems that will make the experience for our many millions of Roku users 100% personalized and unique.

Responsibilities:

Apply state-of-the-art ML on recommendations 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 AB 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.

Help in training and mentoring new team members

Requirements:

5+ years of experience applying Machine Learning to concrete problems at large scale.

Strong CS fundamentals.

Should be able to write an algorithm with ease.

Solid understanding of Data Science and ML fundamentals: - Regression, Classification, Tree-based approach, Neural network, and sequence-based models.

Understanding of NLP approaches like W2V or Bert.

Should be able to identify the right KPIs and Objective functions.

Good understanding of system architecture.

Have experience in big data technologies - streaming architecture, data pipelines, etc.

Bachelors in Computer Science, Statistics, or related field.

Preferred:

Build Recommended Systems for a living.

Experience with Java, Scala, or Python.

Work with big data systems - Spark, EMR, S3 AirFlow.

Hold an MS or PhD in CS or related fields.