Machine Learning Engineer 5 - Ads Measurement
$466,000–$750,000 year
On-siteSeattle, Washington, United States or Los Angeles, California, United States
Job Summary
Build scalable data processing systems and ML-powered measurement solutions for Brand Lift, Incrementality, and Attribution. Develop distributed platforms that enable accurate, privacy-safe, and scientifically rigorous advertising effectiveness measurement. Partner closely with Data Scientists to productionize machine learning models and ensure brand safety during ad serving. This role is within the Ads Measurement Engineering Team at Netflix, a new entrant in the Connected TV advertising space. The team is focused on building highly performant systems to differentiate from competition and become a market leader in record time.
Required Qualifications
- 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
- Proficiency in Java, Python, or Scala
Desired Qualifications
- Experience with causal inference, experimentation, or marketing science
- Experience with streaming and large-scale data processing (e.g., Spark, Flink)
- Experience with MLOps, model serving, and production ML operations
- Experience building customer-facing analytics or measurement platforms
- Experience working in the AdTech or MarTech ecosystem
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