Meta's Monetization RankingAI Research team advances state-of-the-art AI technologies to optimize retrieval, ranking, bidding, and whole page optimization for Meta ads-driving significant annual revenue across Facebook and Instagram. We are seeking a distinguished AI Research Scientist at the technical leadership level to lead foundational and applied research for Ads AI systems. In this role, you will define the long-term research vision for Ads Ranking models, spanning areas such as generative retrieval, generative ranking, LLM-RecSys, large-scale model architectures, and ML systems co-design. You will shape research programs that influence Meta's advertising ecosystem and the broader AI research community, translating breakthrough findings into scalable, real-world impact.
Responsibilities
Define and champion a multi-year research vision for Ads AI systems, identifying transformative opportunities in areas such as generative ranking, whole page optimization, large-scale model architectures, and LLM-based recommendation systems
• Lead the design and execution of novel AI research programs in retrieval and ranking, advancing state-of-the-art techniques for personalized ads delivery at scale
• Architect end-to-end AI systems and modeling frameworks for ads ranking that establish extensible technical foundations and standards adopted across multiple research and engineering organizations
• Drive research on next-generation sequence learning, graph-aware LLMs, AutoML, reinforcement learning, and causal learning for ads optimization
• Lead research on ML systems and hardware-software co-design, including quantization, compression, ML compilers, and resource-efficient AI for next-gen hardware (GPUs, MTIA)
• Define new evaluation metrics and experimental methodologies for long-term, cross-team AI research initiatives, connecting them to revenue and engagement priorities
• Influence technical strategy and roadmap across multiple AI research teams and cross-functional partners, acting as a primary point of expertise for leadership
• Produce high-impact publications at premier AI venues (NeurIPS, ICML, ICLR, KDD, WWW, ACL) and contribute to Meta's research reputation
• Mentor and coach engineers and researchers across the organization, providing customized guidance on research design, modeling approaches, and career development
• Partner with product, engineering, and infrastructure teams to translate research advances into reliable AI systems deployed at Meta's ads scale
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of experience in AI research, spanning both foundational research and applied machine learning in an industry, academic, or government research setting
• Demonstrated track record of leading AI research programs of significant scope, including defining research agendas and delivering results that advance the field
• Extensive publication and citation history in peer-reviewed AI venues such as NeurIPS, ICML, ICLR, CVPR, ACL, or equivalent
• Experience developing and deploying large-scale AI or machine learning systems, including deep expertise in areas such as large language models, generative models, multimodal learning, or AI reasoning
• Experience communicating complex AI research strategy and technical decisions to diverse audiences, including research peers, engineering leaders, and executive stakeholders
Preferred Qualifications
• Experience building and mentoring high-performing research teams, including developing researchers into cross-functional technical leaders
• Experience with ads ranking, recommendation systems, or large-scale retrieval systems
• Experience with generative models, LLMs for recommendation, reinforcement learning, or causal inference in production settings
• Track record of industry-recognized contributions that have measurably influenced the direction of the AI research community
• PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related technical field
