Machine Learning Engineer 5 - Ads Measurement
About The Position
Netflix is hiring a Machine Learning Engineer for its Ads Measurement Engineering team. The team builds scalable platforms and services for advertising measurement, including distributed data-processing systems and machine-learning-powered solutions for Brand Lift, Incrementality, Attribution, and Measurement Insights. These products support accurate, privacy-safe, and scientifically rigorous measurement of advertising effectiveness. The role contributes to building high-performance advertising systems and delivering business impact as Netflix expands its ad-supported offering. The broader Ads Platform Engineering organization builds advertising systems and integrations that deliver ads through Netflix’s content-delivery ecosystem, with attention to member experience and advertiser outcomes.
Requirements
- Experience building advertising measurement products, such as Brand Lift, conversion lift and attribution measurement, advertiser A/B testing, or 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 in building scalable backend services and data pipelines.
- Proficiency in Java, Python, or Scala.
Nice To Haves
- Experience with causal inference, experimentation, or marketing science.
- Experience with streaming and large-scale data processing, such as Spark or 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.
Responsibilities
- Build advertising measurement products, such as Brand Lift, conversion lift and attribution measurement, advertiser A/B testing, and Measurement Intelligence.
- Build and operate production machine-learning systems at scale.
- Productionize machine-learning models in close partnership with Data Scientists.
- Build scalable backend services and data pipelines.
Benefits
- Health Plans
- Mental Health support
- 401(k) Retirement Plan with employer match
- Stock Option Program
- Disability Programs
- Health Savings and Flexible Spending Accounts
- Family-forming benefits
- Life and Serious Injury Benefits
- Paid leave of absence programs
- Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off.
- Full-time salaried employees are immediately entitled to flexible time off.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
