Job Description

Meta's XR Technology team is building the next generation of wearable devices, and the machine learning systems that power them depend on high-quality human data captured in controlled, purpose-built environments. Our onsite collection facilities produce the ground-truth datasets that train and validate perception, sensing, and interaction models ahead of hardware milestones.

As a Data Collection Program Manager, you will run onsite data collection programs based out of our primary capture facility, while coordinating collection activity at additional labs and remote or in-field participant sessions. You will translate engineering data requirements into repeatable collection protocols, lead the moderator teams who run capture sessions with participants, and operate the hardware, tooling, and quality systems that make each collection reproducible.

You will partner directly with the research scientists and engineers who consume the data - working alongside technical program managers to define requirements, resolve capture issues, and close the loop on dataset quality - and you will manage the external vendor relationships that supply participant recruitment and onsite staffing capacity. This is a hands-on, facility-based role: capture hardware, participants, and moderator teams are physically located at the primary facility, and day-to-day execution requires being present with them. Collection windows are gated by hardware availability and downstream model training schedules, so success depends on disciplined planning, rigorous quality control, and sound judgment on trade-offs between scope, timeline, and cost.

Responsibilities
Run end-to-end execution of onsite data collection programs at the Fremont capture facility, from requirements intake through dataset delivery and acceptance
* Partner directly with research scientists and engineering teams to translate model and evaluation requirements into executable collection protocols, participant criteria, session designs, and acceptance criteria
* Coordinate collection activity beyond the primary facility - including additional labs and remote or in-field participant collections - keeping protocols, tooling, and quality standards consistent across every location
* Lead, schedule, and develop teams of onsite collection moderators and technicians who operate capture hardware and facilitate participant sessions
* Build and maintain standard operating procedures, training curricula, and certification materials that allow new moderators to reach quality bar consistently and quickly
* Establish and operate quality processes - including calibration routines, gold-standard checks, in-session validation, and post-collection audits - and drive measurable reductions in rework and data rejection rates
* Convert one-off collections into repeatable, documented programs with predictable throughput and turnaround times
* Set up, operate, and troubleshoot prototype and pre-release capture hardware, sensor rigs, and multi-device synchronization setups; partner with hardware and firmware engineers to triage and resolve capture failures
* Manage day-to-day relationships with external vendors supporting participant recruitment and onsite staffing, including scoping, requirements handoff, performance tracking, and escalation
* Align requirements, timelines, and budgets across engineering stakeholders, vendor partners, and facility capacity; track spend against forecast and re-prioritize as hardware and training schedules shift
* Serve as the primary point of contact for data consumers - communicating collection status, quality metrics, known limitations, and dataset documentation
* Ensure collections meet participant consent, privacy, data handling, and safety requirements, partnering with legal, privacy, and research review partners
* Track and report program health metrics - throughput, quality rates, schedule adherence, and budget consumption - to stakeholders at varying leadership levels

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
* 4+ years of experience in program management, research operations, or technical operations, including direct involvement in onsite or lab-based data collection, user studies, or hardware testing programs
* Hands-on experience with hardware - prototype devices, sensors, capture rigs, or test equipment - including setup, calibration, and failure triage
* Experience coordinating or leading onsite operators, moderators, technicians, or contingent staff, including scheduling and day-to-day direction
* Experience authoring standard operating procedures, training materials, or operational documentation for hands-on teams
* Experience establishing quality control processes and using operational metrics to drive measurable improvement
* Experience working with external vendors or staffing partners, including requirements handoff and performance tracking
* Experience translating technical requirements from engineering or research stakeholders into executable operational plans, and communicating status, risks, and trade-offs back to them Experience in AR/VR, wearables, consumer electronics, or other hardware-gated development environments
* Experience coordinating operations across multiple physical sites or supporting remote data collection at scale
* Experience with privacy, consent, and data governance requirements applicable to human-subject or biometric data
* Experience standing up a new lab, studio, or collection facility, or scaling an existing one
* Demonstrated ability to integrate AI tools and workflow automation to optimize operational processes and drive measurable impact (e.g., efficiency gains, quality improvements)
* Experience with multi-sensor or multi-device synchronized capture, sensor calibration, or biometric and physiological sensing
* Experience collecting data for machine learning applications, including ground-truth annotation, dataset curation, or model evaluation datasets
* Familiarity with participant recruitment operations, screening criteria design, and informed consent processes for human-subject data collection