Technical Program Manager, AI/ML

The Meta Technical Program Management (TPM) community is pioneering technologies to bring people (and businesses) closer together at a global scale. TPMs work at the cross-section between technical execution and business strategy and are expected to partner closely with Engineering and Product teams. Being a TPM at Meta means driving impact by delivering measurable results across a wide range of areas. You'll be responsible for defining and guiding high-level goals and roadmaps, monitoring and communicating progress, and defining functional requirements for new products and features. It also means having a solid technical background with experience in system architecture and cross-functional collaboration, understanding system architecture, and the experience to effectively collaborate across functions and organizations to deliver impact.

As a Technical Program Manager (TPM), for the Monetization Ranking and Foundations AI team, you will be responsible for delivering significant business value through ML innovations and development of State of the Art Ads Recommendation technologies. You will work with Infra and ML Ranking teams of talented ML engineers, product managers, data scientists, and other cross-functional team members to build state of the art Modeling techniques and build effective tools (and strategy) to streamline model productionization process while maintaining defined quality standards throughout the model development lifecycle.

You’ll communicate progress and drive program execution efficiently through cross-functional and cross-organizational collaboration to achieve business goals. You’ll be an integral part of the team who will drive technical strategy, system architectural discussions, and make future-proof decisions that align with product strategy and vision.

Responsibilities

Develop and manage end-to-end technical AI/ML product solutions and ensure on-time delivery
Manage and own cross-functional products and programs execution in a matrix organization
Drive and influence technical and product strategy, proactively identify risks and develop mitigation strategies, align on priorities, and set direction for a broadly cross-functional area
Help define the roadmap and long-term strategy of the teams that you are working with
Design measurements to track impact and drive internal process improvements
Communicate the technology, requirements, goals and milestones of your team
Move fast in a flat organization by working in concert with technical program managers, product managers and engineers across Meta to establish a shared vision for improving execution and building solutions
Ongoing communication of planning, project status, issues and risks in a timely fashion to stakeholders
Help drive product decisions to align with broader company initiatives

Qualifications

B.S. in Computer Science or a related technical discipline, or equivalent experience
10+ years of software engineering, systems engineering, hardware engineering, or technical product/program management experience
Experience driving and delivering complex AI/ ML tech programs or products from inception to delivery
Experience defining strategic direction and identifying new opportunities for impact amongst products, platforms and programs
Knowledge of user needs, gathering requirements, and defining scope
Experience operating independently across multiple teams and functions, demonstrated critical thinking, and thought leadership
Communication experience at executive level and experience influencing Leadership and technical management teams to develop systems, solutions, and products
Experience prioritizing and coordinating competing workstreams based on impact, deadlines, and stakeholder needs
Analytical and problem-solving experience with large-scale systems
Experience establishing work relationships across multi-disciplinary teams and multiple partners in different time zones Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Knowledge of digital advertising platforms and ads monetization strategies
Experience with AI training environments and resource capacity planning
Knowledge of Recommender Systems (RecSys), Machine Learning (ML) and Artificial Intelligence (AI) concepts, including their impact on infrastructure
Familiarity with ML development workflows, model lifecycle management, and experimentation frameworks
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Hands-on experience building machine learning models and/or recommender systems, with the ability to clearly explain foundational ML concepts
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies