Ads is the largest revenue generator at Meta and Ads Quality represents around 20% of total revenues which are used to generate long term ads and organic engagement. Core Ads Quality is a unique team jointly optimizing for both quality and revenue, aiming at making this investment more revenue / quality trade-off efficient and generate long term revenue growth through user learning. Among others, Core Ads Quality focuses on: * Finding the right trade-off between short and long term revenues * Standardizing and optimizing quality treatment of ads across surfaces and page types * Understanding user behavior with respect to ads quality * Building a solid infrastructure around signals, labels and quality metrics We work at the intersection of Ads, Machine Learning and User Behavior understanding. The nature of our work is very analytical, involving collaboration with our Data Scientist and a heavy focus on not only understand “what” but also “why”. Despite having been created a couple of years ago, the Ads Quality space at Meta is still nascent and full of unexploited opportunities. The org is further structured into the following teams/sub-pillars: * Integrity & Efficiency: Proactively cover long-term revenue risks from advertiser friction while supporting cross-functional teams with delivery expertise. * Ads Conversion Familiarity: Accelerate Non-Purchaser (NP) -> Purchaser (P) transition by increasing familiarity of ads for users who don't interact with ads frequently * Post-Click Quality: Stop Purchaser (P) to Non-Purchaser (NP) user conversions from bad purchase experiences. * Modeling: Enhance quality and drive long-term revenue growth through modeling. * Quality Science: Build the foundational end to end understanding for funnel quality signals to ensure the efficiency, health and coverage. The team has consistently hit their goals and delivered XXXM$ in incremental long term revenue for Meta while ensuring high ads quality.
Responsibilities
Work on meaningful technical (ML and infra) problems at Meta’s scale affecting multiple surfaces (Facebook, Instagram, Threads,...) Fundamentally change how decisions are made across the business when investing on ads quality Develop novel, accurate AI algorithms and advanced systems for large scale applications Define long-term plans and lead teams on executing them Improve the experience of users interacting with ads and help the company mission to establish valuable connections between users and businesses Lead projects with clear top-line metric impact Ensure Ads Quality is at the forefront of AI technologies
Qualifications
Bachelor's degree in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience Experience in bringing research results into production Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use Experience developing machine learning algorithms or machine learning infrastructure in Python, PyTorch, and/or C/C++ Track record delivering successful products with large scale impact Experience in User Behaviour modeling, Long-term Value optimization or Causal Learning Experience in Reinforcement Learning, GenAI, Large Language Models, etc PhD in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience Experience in Ads, especially in auction theory and implementation (bidding, budgeting, targeting)