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Netflix

Machine Learning Engineer 5 - Ads Measurement

Salary$466k – $750k
LocationLos Angeles,California,United States of America
Work moderemote
Typefull-time
SenioritySenior
DepartmentData & Insights
EquityIncluded
Company size10,000+ people
First seenSep 18, 2026 · 3w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Must have5
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 have5
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
Skills
Java
Python
Scala
Spark
Flink
MLOps
Benefits
Health insurance
Mental health
401(k)
Stock option program
Disability programs
Health savings account
Flexible spending accounts
Family forming benefits
Life insurance
Serious injury benefits
Paid leave
Unlimited PTO
About the company
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.
Benefits
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.
Legal
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.
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