
Program Manager, Product Data Operations
Required skills
- AI solutions
- product data operations
- AI model training
- data quality
- annotation workflows
- AI-driven features
- data requirements
- quality standards
- data collection
- data labeling
Nice to have
- prompt engineering
- context engineering
- agent orchestration
- emerging AI technologies
- outsourced data annotation
- bias mitigation
Role summary
Meta is looking for a Program Manager to lead AI solutions and product data operations programs for the Superintelligence Lab. This role involves overseeing AI model training pipelines, data quality, and annotation workflows to ensure high-quality data for AI-driven features. The Program Manager will collaborate with researchers, engineers, and product teams to define strategies, resolve dependencies, and implement scalable solutions. Key responsibilities include managing cross-functional programs, identifying and resolving data operation bottlenecks, developing program documentation, tracking health metrics, and leveraging AI tools for efficiency. The role requires 6+ years of experience in program management or data operations supporting AI/ML development, with a fundamental understanding of the AI/ML model lifecycle and data requirements.
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
Minimum Qualifications
- 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
Preferred Qualifications
- 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
- 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
- Experience managing vendor or outsourced data annotation and labeling operations at scale
- Master's degree in Computer Science, Artificial Intelligence, Computer Engineering, Human-Computer Interaction, or a related technical field
- Experience working directly with research or machine learning teams to define data requirements and evaluate the quality of datasets for AI model development
- Familiarity with data governance practices, metadata management, or compliance considerations relevant to AI training data
$132,000/year to $189,000/year + bonus + equity + benefits
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