Software Engineer 5 - Ads Forecasting and Simulation

Netflix•Los Gatos, CA

4d•$388,000 - $558,000

About The Position

Netflix launched a new ad-supported tier in November 2022 to offer members more choice in how they consume their content. This new tier allows Netflix to attract new members at a lower price point, while also creating a compelling path for advertisers to reach audiences that are deeply engaged. The Ads Platform Engineering teams build advertising systems and integrations that power the delivery of ads using Netflix's world-class content delivery ecosystem. The 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. Simulation supports experimentation, analytics, scenario planning, pricing, and packaging use cases. The team needs to build distributed systems that are highly efficient and scalable to handle large and growing ads data and intense computation, while remaining easy to add, reuse, and enhance. The team also needs to work closely with the science team to productionize ML models and optimization algorithms. This team is new and faces the ambition of building highly performant advertising systems and delivering high impact to the business by monetizing Netflix's content. As one of the newest entrants in the rapidly growing Connected TV advertising space, the team seeks to build unique value propositions to differentiate from the competition and become a market leader.

Requirements

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.

Nice To Haves

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.

Responsibilities

Build sophisticated ads forecasting systems which involves ML models.
Build high performance ad server simulation that accounts for constraints like frequency capping, targeting, publisher policy, and other business parameters.
Handle data at extremely large volumes with big data tools like Spark.
Build high throughput low latency distributed systems that utilized the big data.
Work with cross-functional teams to drive large and complex projects.
Productionize ML models and optimization algorithms.
Productionize ML models and deploy models at scale.
Work on industry consortium efforts or working groups.
Ensure advertiser brand safety during serving.
Ensure members only see the most appropriate ads for them.