Meta
Reality Labs Product Data Operations Program Manager
$99K–$144K
Fremont, CA · Manager · Full-time · Posted Oct 8, 2026
- Experience
- 4+ years in program management, operations, or technical operations within a hardware, research, or data-driven organization.
- Education
- Bachelor's degree in a directly related field, or equivalent practical experience; degree must be completed prior to joining Meta.
About the job
Runs end-to-end human-data collection programs for Reality Labs, scaling data processing and quality checks with AI and automation and evaluating data and model performance.
What you'll do
- Manage onsite, lab, and remote data collections from requirements through dataset delivery, including protocols, staffing, and vendor coordination.
- Operate prototype capture hardware and establish collection quality, safety, consent, and privacy processes.
- Build AI and automation workflows, evaluation practices, and operational metrics to improve data quality and throughput.
What they ask for
- 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, operations, or technical operations within a hardware, research, or data-driven organization.
- Analytical experience using data to identify trends, diagnose operational issues, and influence program direction.
- Experience building or deploying automation or AI solutions in production workflows.
Nice to have
- Familiarity with AI or ML development lifecycles, including model evaluation, benchmarking, and deployment processes.
- Experience with machine-learning data collection, synchronized capture, sensor calibration, human-subject data, or hardware-based development.
Pay
$99,000/year to $144,000/year (base salary)
Tools
AI, ML, prototype and pre-release capture hardware, sensor rigs, multi-device synchronization setup, dashboards
AI focus
Deploys AI and automation for pre-annotation, quality triage, and workflow automation; builds evaluation practices including gold-standard datasets, model-versus-human comparison, and accuracy thresholds.
Model-written summary · the original posting is authoritative