Software Engineering Manager, Ads Systems

Meta is seeking an Engineering Manager to own and lead an area within Core Ads Quality, building the systems that determine the quality of ads people see across Facebook, Instagram, and Messenger. In this role, you will be accountable for an area of Meta's ads delivery stack - from quality signals and prediction models to ranking and auction mechanisms, large-scale experimentation, and long-term measurement.

You will set the vision and technical strategy for how ad quality is modeled, priced, and protected in the auction, balancing short-term revenue with long-term value for people and businesses. You will partner closely with product, data science, data engineering, and integrity to deliver changes that have measurable impact on billions of people and millions of advertisers.

• Significant experience in software engineering, including work on large-scale production systems such as ads delivery, ranking, recommendation, search, or marketplaces
• Experience managing engineers, including ownership of a broad technical area with accountability for its strategy and outcomes
• Experience driving technical strategy and roadmap decisions for large-scale ranking, auction, or ML-driven production systems
• Experience with online experimentation (A/B testing) and using data to make launch decisions that balance competing metrics
• Experience partnering cross-functionally with product, data science, and other engineering groups to define problem scope and deliver measurable outcomes
• Experience recruiting, developing, and retaining engineering talent in ambiguous, high-impact areas
• Hands-on background in ML model development and production ML systems (e.g., PyTorch), including multi-objective ranking and calibration
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize or redesign engineering workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience building shared infrastructure and platforms used across an organization, with a focus on reliability, developer productivity, and efficiency
• Experience with ad quality, user experience, or integrity signals in ranking (e.g., quality bids, negative feedback, post-click and post-purchase quality, low-quality and harmful content)
• Track record of building ads delivery, ranking, or auction systems that directly influenced revenue and user experience metrics at significant scale
• Experience with auction and mechanism design, bid optimization, or marketplace health, including advertiser-side considerations
• Experience leading engineers across multiple sites
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience measuring long-term effects of product changes (e.g., holdouts, long-term causal inference, user learning effects)