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Netflix

Machine Learning Engineer 5 - Ads Signals & Targeting

Reposted 13 Days Ago
Remote
Hiring Remotely in USA
466K-750K Annually
Entry level
Remote
Hiring Remotely in USA
466K-750K Annually
Entry level
Build and deploy low-latency machine learning models and inference infrastructure for Netflix’s advertising platform. Develop identity resolution, behavioral and contextual targeting, lookalike expansion, user signals, and audience features at massive scale. Collaborate with science, product, engineering, operations, design, and research teams to productionize models while supporting privacy, governance, security, and advertiser brand safety.
The summary above was generated by AI

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.

Our team is growing to meet ambitious goals: building highly performant advertising systems to effectively monetize our incredible slate of content and deliver real impact for the business. 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.

The Ads Signals & Targeting team is revolutionizing ad experiences by utilizing advanced machine learning models for identity resolution and optimal behavioral and contextual audience targeting. We create foundational systems that deliver relevant and engaging ads to Netflix members, all while upholding their privacy. Our continuous refinement of models generates a flywheel effect, enhancing member experiences and driving optimal advertiser outcomes at scale.

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 in building end-to-end ML model deployment and inference infra for low-latency real-time ad systems.

  • Experience building machine learning models for ads targeting and lookalike expansion.

  • Professional experience in designing and building user and contextual signals and audience targeting features for ad platforms.

  • Proficiency in Java, C++, Python, or Scala with a solid understanding of multi-threading and memory management.

  • Experience in handling data at extremely large volumes with big data tools like Spark.

  • Collaborate with cross-functional stakeholders from the science team, product, engineering, operations, design, consumer research, etc., to productionize and deploy models at scale

Nice to haves:
  • Strong understanding of data privacy, governance, and security concepts, including Privacy by Design principles.

  • Experience with ads targeting using machine learning models.

  • Experience working in the CTV space and knowledge of its unique constraints.


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. This compensation range will vary based on location.

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.

Job is open for no less than 7 days and will be removed when the position is filled.

HQ

Netflix Los Gatos, California, USA Office

100 Winchester Circle, Los Gatos, CA, United States

Netflix San Jose, California, USA Office

San Jose, United States, 0

Netflix Santa Clara, California, USA Office

Santa Clara, United States, 0

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