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Machine Learning Engineer 5 - Ads

Netflix

Software and Technology Jobs

Machine Learning Engineer 5 - Ads

full-timePosted: Oct 16, 2025

Job Description

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time. We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming 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 deeply engaged audiences.Our Team:The Core Ads Algorithms team is the engine behind the intelligence that powers ad personalization at Netflix. Our mission is to develop innovative, data-driven solutions that deliver highly relevant ad experiences to our members and drive impactful results for advertisers—all while maintaining the exceptional quality and personalization that define the Netflix experience.Responsibilities:Bridge software engineering and machine learning research by developing efficient, scalable, and maintainable machine learning models and services that meet high QPS and low-latency requirements.Collaborate closely with machine learning researchers to operationalize research and ensure seamless integration of models into production environments.Enhance the performance and scalability of machine learning models to effectively accommodate the increasing demand for advertising and the implementation of novel ad optimization objectives.Collaborate closely with machine learning scientists, infrastructure engineers, and product managers to shape the ML infrastructure for Netflix Ads.Optimize the performance and scalability of machine learning models to support increasing ad demand and the introduction of new ad objectives.Contribute to the ongoing enhancement of company-wide ML infrastructure and tooling, ensuring we remain at the forefront of industry best practices.Stay current with state-of-the-art computing and machine learning technologies.Design and Build Advanced Models: Develop and deploy cutting-edge machine learning and statistical models for ad ranking, pacing and personalization—ensuring the right ad reaches the right audience at the right moment.Drive Business Impact: Work on high-impact problems that directly influence Netflix’s new and expanding revenue stream, shaping the future of advertising in premium streaming.Innovate at Scale: Tackle some of the most exciting technical challenges in the industry, leveraging Netflix’s world-class infrastructure and massive datasets to create scalable, real-time solutions.Collaborate Across Disciplines: Partner with engineers, data scientists, product managers, and business leaders to translate business needs into technical breakthroughs and measurable outcomes.Champion User Experience: Balance advertiser goals with viewer satisfaction, building algorithms that respect privacy, enhance relevance, and maintain the seamless streaming experience Netflix is known for.Lead with Science: Stay at the forefront of research in machine learning, optimization, and data science, and bring the latest advancements into production.Shape the Future: Be part of a team that’s setting the standard for ad-supported streaming, with the opportunity to influence strategy, best practices, and the evolution of a high-profile product.Qualifications:Proficiency in Java, Python, or Scala.Experience in building end-to-end ML model deployment for real-time systems.Skilled at maintaining production systems, with familiarity in DevOps tools and practices.Strong problem-solving and cross-functional collaboration skills. 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 $100,000 - $720,000.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.Job is open for no less than 7 days and will be removed when the position is filled.

Locations

  • Washington, United States of America (Remote)

Salary

100,000 - 720,000 USD / yearly

Estimated Salary Rangehigh confidence

250,000 - 400,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Proficiency in Java, Python, or Scalaintermediate
  • Experience in building end-to-end ML model deployment for real-time systemsintermediate
  • Skilled at maintaining production systems, with familiarity in DevOps tools and practicesintermediate
  • Strong problem-solving and cross-functional collaboration skillsintermediate

Required Qualifications

  • Proficiency in Java, Python, or Scala. (experience)
  • Experience in building end-to-end ML model deployment for real-time systems. (experience)
  • Skilled at maintaining production systems, with familiarity in DevOps tools and practices. (experience)
  • Strong problem-solving and cross-functional collaboration skills. (experience)

Responsibilities

  • Bridge software engineering and machine learning research by developing efficient, scalable, and maintainable machine learning models and services that meet high QPS and low-latency requirements.
  • Collaborate closely with machine learning researchers to operationalize research and ensure seamless integration of models into production environments.
  • Enhance the performance and scalability of machine learning models to effectively accommodate the increasing demand for advertising and the implementation of novel ad optimization objectives.
  • Collaborate closely with machine learning scientists, infrastructure engineers, and product managers to shape the ML infrastructure for Netflix Ads.
  • Optimize the performance and scalability of machine learning models to support increasing ad demand and the introduction of new ad objectives.
  • Contribute to the ongoing enhancement of company-wide ML infrastructure and tooling, ensuring we remain at the forefront of industry best practices.
  • Stay current with state-of-the-art computing and machine learning technologies.
  • Design and Build Advanced Models: Develop and deploy cutting-edge machine learning and statistical models for ad ranking, pacing and personalization—ensuring the right ad reaches the right audience at the right moment.
  • Drive Business Impact: Work on high-impact problems that directly influence Netflix’s new and expanding revenue stream, shaping the future of advertising in premium streaming.
  • Innovate at Scale: Tackle some of the most exciting technical challenges in the industry, leveraging Netflix’s world-class infrastructure and massive datasets to create scalable, real-time solutions.
  • Collaborate Across Disciplines: Partner with engineers, data scientists, product managers, and business leaders to translate business needs into technical breakthroughs and measurable outcomes.
  • Champion User Experience: Balance advertiser goals with viewer satisfaction, building algorithms that respect privacy, enhance relevance, and maintain the seamless streaming experience Netflix is known for.
  • Lead with Science: Stay at the forefront of research in machine learning, optimization, and data science, and bring the latest advancements into production.
  • Shape the Future: Be part of a team that’s setting the standard for ad-supported streaming, with the opportunity to influence strategy, best practices, and the evolution of a high-profile product.

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Netflix logo

Machine Learning Engineer 5 - Ads

Netflix

Software and Technology Jobs

Machine Learning Engineer 5 - Ads

full-timePosted: Oct 16, 2025

Job Description

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time. We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming 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 deeply engaged audiences.Our Team:The Core Ads Algorithms team is the engine behind the intelligence that powers ad personalization at Netflix. Our mission is to develop innovative, data-driven solutions that deliver highly relevant ad experiences to our members and drive impactful results for advertisers—all while maintaining the exceptional quality and personalization that define the Netflix experience.Responsibilities:Bridge software engineering and machine learning research by developing efficient, scalable, and maintainable machine learning models and services that meet high QPS and low-latency requirements.Collaborate closely with machine learning researchers to operationalize research and ensure seamless integration of models into production environments.Enhance the performance and scalability of machine learning models to effectively accommodate the increasing demand for advertising and the implementation of novel ad optimization objectives.Collaborate closely with machine learning scientists, infrastructure engineers, and product managers to shape the ML infrastructure for Netflix Ads.Optimize the performance and scalability of machine learning models to support increasing ad demand and the introduction of new ad objectives.Contribute to the ongoing enhancement of company-wide ML infrastructure and tooling, ensuring we remain at the forefront of industry best practices.Stay current with state-of-the-art computing and machine learning technologies.Design and Build Advanced Models: Develop and deploy cutting-edge machine learning and statistical models for ad ranking, pacing and personalization—ensuring the right ad reaches the right audience at the right moment.Drive Business Impact: Work on high-impact problems that directly influence Netflix’s new and expanding revenue stream, shaping the future of advertising in premium streaming.Innovate at Scale: Tackle some of the most exciting technical challenges in the industry, leveraging Netflix’s world-class infrastructure and massive datasets to create scalable, real-time solutions.Collaborate Across Disciplines: Partner with engineers, data scientists, product managers, and business leaders to translate business needs into technical breakthroughs and measurable outcomes.Champion User Experience: Balance advertiser goals with viewer satisfaction, building algorithms that respect privacy, enhance relevance, and maintain the seamless streaming experience Netflix is known for.Lead with Science: Stay at the forefront of research in machine learning, optimization, and data science, and bring the latest advancements into production.Shape the Future: Be part of a team that’s setting the standard for ad-supported streaming, with the opportunity to influence strategy, best practices, and the evolution of a high-profile product.Qualifications:Proficiency in Java, Python, or Scala.Experience in building end-to-end ML model deployment for real-time systems.Skilled at maintaining production systems, with familiarity in DevOps tools and practices.Strong problem-solving and cross-functional collaboration skills. 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 $100,000 - $720,000.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.Job is open for no less than 7 days and will be removed when the position is filled.

Locations

  • Washington, United States of America (Remote)

Salary

100,000 - 720,000 USD / yearly

Estimated Salary Rangehigh confidence

250,000 - 400,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Proficiency in Java, Python, or Scalaintermediate
  • Experience in building end-to-end ML model deployment for real-time systemsintermediate
  • Skilled at maintaining production systems, with familiarity in DevOps tools and practicesintermediate
  • Strong problem-solving and cross-functional collaboration skillsintermediate

Required Qualifications

  • Proficiency in Java, Python, or Scala. (experience)
  • Experience in building end-to-end ML model deployment for real-time systems. (experience)
  • Skilled at maintaining production systems, with familiarity in DevOps tools and practices. (experience)
  • Strong problem-solving and cross-functional collaboration skills. (experience)

Responsibilities

  • Bridge software engineering and machine learning research by developing efficient, scalable, and maintainable machine learning models and services that meet high QPS and low-latency requirements.
  • Collaborate closely with machine learning researchers to operationalize research and ensure seamless integration of models into production environments.
  • Enhance the performance and scalability of machine learning models to effectively accommodate the increasing demand for advertising and the implementation of novel ad optimization objectives.
  • Collaborate closely with machine learning scientists, infrastructure engineers, and product managers to shape the ML infrastructure for Netflix Ads.
  • Optimize the performance and scalability of machine learning models to support increasing ad demand and the introduction of new ad objectives.
  • Contribute to the ongoing enhancement of company-wide ML infrastructure and tooling, ensuring we remain at the forefront of industry best practices.
  • Stay current with state-of-the-art computing and machine learning technologies.
  • Design and Build Advanced Models: Develop and deploy cutting-edge machine learning and statistical models for ad ranking, pacing and personalization—ensuring the right ad reaches the right audience at the right moment.
  • Drive Business Impact: Work on high-impact problems that directly influence Netflix’s new and expanding revenue stream, shaping the future of advertising in premium streaming.
  • Innovate at Scale: Tackle some of the most exciting technical challenges in the industry, leveraging Netflix’s world-class infrastructure and massive datasets to create scalable, real-time solutions.
  • Collaborate Across Disciplines: Partner with engineers, data scientists, product managers, and business leaders to translate business needs into technical breakthroughs and measurable outcomes.
  • Champion User Experience: Balance advertiser goals with viewer satisfaction, building algorithms that respect privacy, enhance relevance, and maintain the seamless streaming experience Netflix is known for.
  • Lead with Science: Stay at the forefront of research in machine learning, optimization, and data science, and bring the latest advancements into production.
  • Shape the Future: Be part of a team that’s setting the standard for ad-supported streaming, with the opportunity to influence strategy, best practices, and the evolution of a high-profile product.

Target Your Resume for "Machine Learning Engineer 5 - Ads" , Netflix

Get personalized recommendations to optimize your resume specifically for Machine Learning Engineer 5 - Ads. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Machine Learning Engineer 5 - Ads" , Netflix

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

Data & InsightsStreaming

Answer 10 quick questions to check your fit for Machine Learning Engineer 5 - Ads @ Netflix.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.