Staff ML Engineer — Ad Serving & Real-Time Auctions

Roku; Boston (MA); Hybrid; USD 196,000 - 435,000; Full time

Benefits offered by this job

Health insurance

Equity awards

Life insurance

Disability benefits

Parental leave

Wellness benefits

Paid time off

Job summary

Roku seeks a staff-level machine learning engineer to lead marketplace intelligence and demand optimization for the Ad Serving platform in Massachusetts. You will translate business problems into hypotheses, build ML models, run live experiments, and deploy production ML systems for low-latency ad serving.

Ideal candidates have 10+ years in ML/data science, strong statistics/optimization knowledge, and hands-on software engineering with Python/SQL/Java or Scala, plus track record leading

Qualifications

• 10+ years of ML/Data Science experience applying ML to real-world problems.
• Deep expertise in statistics, ML, and optimization techniques.
• Hands-on ML model development, deployment, monitoring, and improvement.
• Solid software engineering skills: Python/SQL/Java or Scala.
• Strong communication and cross-functional leadership.

Responsibilities

• Translate business problems into testable hypotheses and objectives.
• Develop ML models to drive product innovation and business outcomes.
• Design and run live experiments to validate improvements.
• Build production-grade ML systems for large-scale ad serving.
• Partner with stakeholders to define ML strategy for Ad Serving.
• Provide technical leadership in ML, experimentation, and applied research.

Skills

Machine learning

Python

SQL

Java/Scala

Statistics

CS fundamentals

Leadership

Communication

Cross-functional collaboration

Job description

Roku seeks a staff-level machine learning engineer to lead marketplace intelligence and demand optimization for the Ad Serving platform in Massachusetts. You will translate business problems into hypotheses, build ML models, run live experiments, and deploy production ML systems for low-latency ad serving.

Ideal candidates have 10+ years in ML/data science, strong statistics/optimization knowledge, and hands-on software engineering with Python/SQL/Java or Scala, plus track record leading