Product Data Operations Program Manager

Meta is seeking a Program Manager to lead AI solutions and product data operations programs that support our AI Monetization & Foundational products. Meta is seeking a Product Operations Manager to support the Central and Standalone Products organization.

In this role, you will oversee end-to-end data operations programs spanning AI model training pipelines, data quality initiatives, and annotation workflows — ensuring that product teams have the high-quality data they need to build and scale AI-driven features.

You will collaborate closely with researchers, engineers, product, and operations partners to define program strategies, resolve cross-functional dependencies, and translate complex data challenges into actionable, scalable solutions.

Responsibilities

• Manage and deliver product data operations programs that support AI model training, evaluation, and deployment pipelines across multiple product teams
• Partner with research, engineering, and product teams to define data requirements, align on quality standards, and prioritize data collection and annotation efforts for AI solutions
• Identify and resolve bottlenecks in data labeling, annotation, and curation workflows to ensure timely delivery of high-quality training datasets
• Break down complex data operations challenges into manageable components, applying systematic analysis to design and implement scalable solutions aligned with AI product roadmaps
• Develop and maintain program documentation including data governance frameworks, workflow specifications, risk registers, and milestone tracking for AI data initiatives
• Engage team leaders and cross-functional stakeholders to build alignment on program direction, surface risks proactively, and drive decisions that unblock data operations work
• Track and communicate program health metrics — including data throughput, quality rates, and delivery timelines — adapting communication style and format to technical and non-technical audiences
• Leverage AI tools and workflow automation to improve the efficiency and quality of data operations processes, sharing learnings to scale adoption across the team
• Contribute to team-level goal setting by synthesizing insights from data operations performance and translating them into actionable recommendations for AI product teams
• Adapt program plans in response to shifting AI product priorities, regulatory requirements, or data availability constraints, maintaining focus on highest-impact deliverables

Qualifications

• Currently has, or is in the process of obtaining a Bachelor's degree in a directly related field, or equivalent practical experience. Degree must be completed prior to joining Meta
• 6+ years of experience in program management, data operations, or technical operations roles supporting AI, machine learning, or data-driven product development; or 2+ years of such experience with a Bachelor's degree in Computer Science, Artificial Intelligence, Computer Engineering, Human-Computer Interaction, or a related technical field
• Fundamental understanding of AI/ML model development and the data requirements across the model lifecycle — including training, evaluation, and fine-tuning data needs
• Experience managing cross-functional programs involving data pipelines, data labeling, annotation workflows, or AI training data quality initiatives
• Experience in analyzing operational data and communicating findings and recommendations to technical and non-technical stakeholders at varying levels of leadership
• Experience identifying process inefficiencies and implementing scalable solutions within data or AI operations environments Master's degree in Computer Science, Artificial Intelligence, Computer Engineering, Human-Computer Interaction, or a related technical field
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience working directly with research or machine learning teams to define data requirements and evaluate the quality of datasets for AI model development
• Experience managing vendor or outsourced data annotation and labeling operations at scale
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Familiarity with data governance practices, metadata management, or compliance considerations relevant to AI training data
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience using AI-powered tools or workflow automation platforms to redesign and accelerate data operations processes, including demonstrated application of responsible and ethical AI practices such as bias mitigation and quality review