Ranking AI is the central core machine learning org within Meta’s Monetization group, powering Meta’s revenue and business growth by advancing and deploying state-of-art Recommendation Systems AI for our Ads stack. We are currently redesigning the large and fragmented Ads model space by developing new modeling architectures, advancing the scale limit through model-hardware co-design, and developing techniques that better leverage anonymized, aggregated data. While there is significant focus on innovation, we pride ourselves in being able to translate research to production with high velocity, delivering on half on half aggressive revenue targets in a predictable fashion. The ideal candidate will bring hands-on experience in driving product and program growth through machine learning (ML) technologies, with a proven track record of leading AI-powered projects that span across modeling teams and require close collaboration with infrastructure teams. They will have a strong background in building and growing teams and have a comprehensive understanding of the full machine learning lifecycle—from raw data to features and modeling to training, inference, and debugging. Adept in navigating ambiguity and competing priorities, the candidate will thrive in an entrepreneurial, fast-paced environment. They will have a keen ability to sift through complex information, distill key insights, and up-level critical data to drive informed decision-making at all levels. They are not only skilled at leading teams and developing high-level strategic initiatives but are also hands-on, capable of rolling up their sleeves and executing the details to ensure successful program delivery.
Responsibilities
Define and lead technical execution strategy for multiple product and platform areas Articulate the technology, requirements, goals, and milestones of your team Work with engineering and product management leadership to define and revise the long-term strategy for the organization Work with the team to develop end-to-end program plans, influence teams to deliver against them, and keep the org and leadership informed on progress Manage, mentor, and grow the existing product technical program management teams Drive internal process improvements across multiple teams and functions Work with teams to set milestones, communicate program statuses, and identify/address potential setbacks Work with engineering to ensure the team’s work focuses on the highest priority partner team and customer needs Work across organizations to align plans, manage dependencies, drive execution, and deliver broad solutions Build and scale the organization to support multiple fast-paced product categories Responsible for people management - hiring, developing, and implementing organizational structure, delivering performance reviews, providing continual feedback, coaching and career growth
Qualifications
B.S. in Computer Science or a related technical discipline, or equivalent experience 15+ years of software industry experience, including systems engineering, hardware engineering, or technical product/program management experience 10+ years of people management experience leading teams to deliver technical programs or products from inception to delivery Proven communication skills Proven interpersonal skills, including relationship building and collaboration within a multi-disciplinary, cross-functional team Experience building, growing, and leading a technical program management organization through design and execution of large infrastructure, tools and applications Experience in growing organizations and developing a team culture Knowledge of software development processes and ML and AI technologies Analytical and problem-solving experience with large-scale systems Experience in scaling large platform and system growth Experience with online Advertising technologies, applications, and systems Experience with using AI, ML, and Generative AI to build solutions Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies