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
* Standardising and optimise quality treatment of ads across surfaces and page types
* Understanding user behaviour 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 Behaviour understanding. The nature of our work is very analytical, with a solid 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 XI 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) – >Non purchaser (NP) user conversions from bad purchase experiences.
* Modelling: Enhance quality and drive long-term revenue growth through modelling.
* Quality Science: Build the foundational end to end understanding for funnel quality signals to ensure its 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.Software Specialist – AI/ML – Monetisation Responsibilities
- Drive the team’s goals and technical direction to pursue opportunities that make your larger organization more efficient
- Effectively communicate complex features and systems in detail
- Understand industry and company-wide trends to help assess & develop new technologies
- Partner and collaborate with organization leaders to help improve the level of performance of the team and organization
- Identify new opportunities for the larger organization and influence the appropriate people for staffing/prioritizing these new ideas
- Lead long term technical strategy and roadmap for large cross-company efforts
- Suggest, collect and synthesize requirements and create an effective feature and technology roadmap
Minimum Qualifications
- Experience developing machine learning algorithms or machine learning infrastructure in Python, PyTorch, and/or C/C++
- Bachelor in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience
- Experience in bringing research results into production
- Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term mission
- Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
- xperience communicating and working across functions to drive solutions
- Experience in manipulating and analyzing complex, high-volume data from varying sources
- Large experience with machine learning / AI technologies
Preferred Qualifications
- PhD in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience
- Experience in Reinforcement Learning, GenAI, Large Language Models, etc
- Experience in Ads, especially in auction theory and implementation (bidding, budgeting, targeting)
- Experience in User Behaviour modellling, Long-term Value optimization or Causal Learning
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