Machine Learning Engineer 5 - Ads Measurement

Netflix Netflix · Big Tech · Los Gatos, CA +4 · Data & Insights

Machine Learning Engineer at Netflix focused on building scalable platforms and ML-powered measurement solutions for advertising, including Brand Lift, Incrementality, Attribution, and Measurement Insights. The role involves productionizing ML models, building backend services and data pipelines, and operating ML systems at scale within the consumer domain.

What you'd actually do

  1. Build scalable platforms and services that power advertising measurement for Netflix.
  2. Develop distributed data processing systems and ML-powered measurement solutions for products such as Brand Lift, Incrementality, Attribution, and Measurement Insights, enabling accurate, privacy-safe, and scientifically rigorous measurement of advertising effectiveness.
  3. Build and operate production machine learning systems at scale.
  4. Productionize machine learning models and partner closely with Data Scientists.
  5. Build scalable backend services and data pipelines.

Skills

Required

  • Java
  • Python
  • Scala
  • building scalable backend services
  • building scalable data pipelines
  • building and operating production machine learning systems at scale
  • productionizing machine learning models

Nice to have

  • causal inference
  • experimentation
  • marketing science
  • streaming
  • large-scale data processing
  • Spark
  • Flink
  • MLOps
  • model serving
  • production ML operations
  • customer-facing analytics
  • measurement platforms
  • AdTech
  • MarTech ecosystem

What the JD emphasized

  • Experience building advertising measurement products (e.g., Brand Lift, Conversion lift and attribution measurement, advertiser A/B testing, Measurement Intelligence).
  • Experience building and operating production machine learning systems at scale.
  • Experience productionizing machine learning models and partnering closely with Data Scientists.
  • Strong software engineering skills building scalable backend services and data pipelines.

Other signals

  • building scalable platforms and services that power advertising measurement
  • develops distributed data processing systems and ML-powered measurement solutions
  • experience building and operating production machine learning systems at scale
  • experience productionizing machine learning models