Machine Learning Engineer 5 - Ads Measurement

We launched a new ad-supported tier in November 2022 to offer our members more choice in how they consume their content. Our new tier allows us to attract new members at a lower price point, while also creating a compelling path for advertisers to reach audiences that are deeply engaged.

Our Team

The Ads Platform Engineering teams build advertising systems and integrations that powers the delivery of ads using our world class content delivery ecosystem. We use a number of Netflix investments and innovations to power our ads - unique mix of client and server side ad insertions, state of the art content delivery system, ad encoding recipes, content understanding and metadata etc. We deliver ads in a manner that’s thoughtful of our member’s viewing experience and drive great outcomes for advertisers. We also ensure that advertiser brand safety is ensured during serving, members only see the most appropriate ads for them.

Ads Measurement Engineering Team builds scalable platforms and services that power advertising measurement for Netflix. The team develops 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. 

Our team is new and yet faced with the enormous ambitions of building highly performant advertising systems and delivering high impact to our business by monetizing our incredible slate of content. As one of the newest entrants in the Connected TV advertising space that’s rapidly growing, we seek to build unique value propositions that help us differentiate from the competition and become a market leader in record time.

We are looking for highly motivated engineers working in the advertising space who are excited to join us on this journey.

Skills & experience we’re seeking:

• 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.

Nice to haves:

• 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.