Machine Learning Engineer (L5 - Senior) , Ads Inventory Management & Forecasting

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 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 Inventory Management & Forecasting team builds state-of-art realtime inventory forecasting solution leveraging ML models and high performance ad server simulations. The team also builds systems that enable publisher inventory management solutions, which supports various monetization strategies such as dynamic pricing, rate card management, product packaging, inventory split and yield optimization.

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

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

• Productionized predictive models to forecast the effectiveness of advertising campaigns, including metrics like impressions, reach, clicks, conversions, and ROI.

• Building Scalable Simulation solution to model different inventory scenarios, including demand fluctuations, pricing strategies, and inventory allocation.

• Familiar with ads budgeting and pacing systems, models, and algorithms

• General understanding of the advertising marketplace and landscape, with a focus on publisher side challenges like optimizing fill rates and maximizing revenue in the context of inventory management.

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

Nice to haves:

• Good understanding of Lucene index and had experience building Lucene index with large volume of data.

• Familiar with publisher-side ad tech systems including ad servers, bidders, yield optimizers, and their demand-side counterparts (SSPs/DSPs)

• Experience in yield optimization, product recommendation and dynamic allocation of direct/programmatic guaranteed and non-guaranteed inventory

• 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

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 consi