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 TeamThe 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 Inventory Management & Forecasting team is dedicated to developing and maintaining E2E inventory forecasting, underwriting and simulation systems. Forecasting enables near-realtime data-driven decisioning for advertisers, agencies, DSPs and Netflix stakeholders who utilize forecasting to plan, optimize and traffic campaigns. Simulation supports experimentation, analytics, scenario planning, pricing and packaging use cases from Sales, Account, Pricing and Science teams. The forecasting and simulation team needs to build distributed systems that are highly efficient and scalable to handle large and growing ads data and intense computation, while still remaining easy to add, reuse and enhance. The team also needs to work closely with science team to productionize ML models and optimization algorithms.
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:Professional experience in building sophisticated ads forecasting systems which involves ML models and high performance ad server simulation that accounts for constraints like frequency capping, targeting, publisher policy, and other business parameters.
Proven experience in handling data at extremely large volumes with big data tools like Spark, and building high throughput low latency distributed systems that utilized the big data.
General understanding of the advertising marketplace and landscape, with a focus on ad serving flow.
Developed many cloud based applications and comfortable with modern programming languages (preferably object oriented).
Experience in working with cross-functional teams to drive large and complex projects.
Good understanding of Lucene index and had experience building and querying Lucene index with large volume of data.
Experience in productionizing ML models and deploying models at scale.
Contributed to an ads industry technology standard (e.g VAST, OpenRTB) or worked on an industry consortium effort, working group etc.
Familiarity with legal compliance and changing landscape of ads regulations around the world.
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 $388,000.00 - $558,000.00.
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
- Professional experience building ads forecasting systems involving ML models and high-performance ad server simulation accounting for business constraints.
- Proven experience handling extremely large volumes of data with big data tools (e.g., Spark) and building high-throughput, low-latency distributed systems.
- General understanding of the advertising marketplace and ad serving flow.
- Experience developing cloud-based applications and proficiency with modern object-oriented programming languages.
- Experience working with cross-functional teams to deliver large, complex projects.
- Good understanding of Lucene indexing and querying at large scale.
- Experience productionizing and deploying ML models at scale.
- Contributions to ads industry standards (e.g., VAST, OpenRTB) or participation in industry working groups.
- Familiarity with global ads legal/compliance landscape.
- Experience in Connected TV (CTV) advertising and its constraints.
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.
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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.
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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.
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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
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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