Machine Learning Engineer 5 - Ads Measurement

Posted Yesterday
Be an Early Applicant
4 Locations
In-Office
466K-750K Annually
Senior level
News + Entertainment
The Role
Build and operate scalable ML-powered advertising measurement platforms (Brand Lift, Incrementality, Attribution). Develop distributed data processing systems, productionize models, collaborate with data scientists, and implement backend services and data pipelines to deliver privacy-safe, scientifically rigorous ad measurement.
Summary Generated by Built In

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

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.


Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer 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. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Skills Required

  • Experience building advertising measurement products (Brand Lift, Conversion lift, attribution, A/B testing)
  • 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
  • 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

Netflix Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.

  • Fair & Transparent Compensation Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
  • Equity Value & Accessibility Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
  • Healthcare Strength Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.

Netflix Insights

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The Company
HQ: Los Gatos, CA
13,212 Employees
Year Founded: 1997

What We Do

Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

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