You will be responsible for the hands-on bring-up, execution, and quality oversight of internal data collection studies, operating in a highly collaborative and technically demanding cross-functional environmentPlan, execute, and track internal ML data collection studies in close collaboration with researchers, engineers, and scientists across the organization Develop a working understanding of the ML experiments being supported, including model objectives, data requirements, labeling, and evaluation criteria, to ensure datasets quality Bring up and maintain pre-release hardware and software platforms used for data collection, performing hands-on troubleshooting and triage to minimize study disruptions Create and maintain clear technical documentation for hardware/software platform setup, study protocols, and data handling procedures Manage day-to-day logistics of internal study sessions, including scheduling participants, configuring hardware and software setups, and maintaining smooth session flow Collaborate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements before and during study execution Track and communicate study progress, blockers, participant throughput, and dataset status to cross-functional partners and senior stakeholders Identify gaps in existing workflows and take initiative to define, document, and socialize process improvementsBachelor's degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience. Apples ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering our next generation of consumer machine learning features.