Program Manager, Product Data Operations (Reality Labs)

Program Manager, Product Data Operations (Reality Labs) Meta is hiring a Reality Labs Product Data Operations Program Manager to run multilingual data collection (DC) for our language expansion work. Reality Labs builds the next generation of computing across Meta's mixed reality, virtual reality, and wearables products. As we bring AI experiences to more languages and regions, the quality, coverage, and speed of our multilingual data shape how well our models understand and respond to people around the world. In this role, you'll take model and product requirements from intake through delivery. For each request, you'll pick the collection model that fits best: in-house collection, scaled vendor collection, or a mix of both. You'll also build DC practices that can scale and repeat across languages and locales. You'll work across functions with research, engineering, product, quality, legal/privacy, and vendor partners. You'll define and enforce quality standards for data deliverables in a fast-moving environment where priorities shift frequently. Responsibilities Own the full lifecycle of language expansion data collection programs, from requirements intake and scoping through collection, quality assurance, and dataset delivery • Turn model, evaluation, and product requirements into clear collection specs: language and locale coverage, speaker and participant criteria, volume targets, timelines, and acceptance criteria • Choose the right DC model for each need (in-house, scaled vendor, or hybrid) based on quality, speed, cost, coverage, and risk, and explain the tradeoffs to stakeholders • Build repeatable DC playbooks, SOPs, templates, and intake standards so that new languages and locales can launch quickly and consistently • Work closely with research scientists, engineers, TPMs, product, linguists, quality, and privacy partners to align on priorities, dependencies, and success measures • Develop systems that operationalize data to track throughput, cost, and quality trends. Build dashboards and leadership-facing reporting that drive decisions • Prioritize competing requests based on impact, urgency, and stakeholder needs. Iterate on plans as model training schedules change, escalate risks early, and ensure that budget targets are met Minimum 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 • Bachelor's degree in a directly related field, or equivalent practical experience. Degree must be completed before joining Meta • 4+ years of experience in program management, data operations or technical operations in a data-driven, AI/ML or technology organization • Experience in running data collection, annotation, or language data programs, including managing external vendors at scale • Experience in communicating with and influencing multiple cross-functional stakeholders and leaders • Experience defining and maintaining quality standards and acceptance criteria for data deliverables • Analytical experience using data to spot trends, diagnose operational issues, and influence program direction • Experience prioritizing competing workstreams based on impact and deadlines in fast-moving, agile environments with changing priorities • Experience breaking ambiguous problems into component parts to develop solutions • In-person presence at least 3 days per week, with occasional travel required Preferred Qualifications • Experience in owning program budgets, cost forecasting, or per-unit cost tracking • Experience with AI/ML development lifecycles, including model evaluation, benchmarking, and data-centric improvement of model output • Proficiency in one or more languages besides English, as the role supports multilingual data collection programs across multiple regions and locales • Track record of building scalable, repeatable operating models or playbooks for a service function • Experience designing hybrid in-house and vendor sourcing strategies, including cost/quality trade-off analysis • Experience with participant recruitment, screening criteria, informed consent, and data governance for human-subject data across regions • Experience with multilingual, speech, text, or conversational AI data, including localization or language expansion programs • Experience building or deploying automation or AI solutions in production workflows • Experience in AR/VR, wearables, consumer electronics or AI products