ML Data Operations Engineer

Apple • Cupertino, CA

22h

About The Position

Apple's 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. In this role, you will work shoulder-to-shoulder with full-time Apple scientists and engineers, not just coordinating logistics, but developing a genuine technical understanding of the ML experiments you support. 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 environment.

Requirements

• Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience.
• Experience supporting or executing human user studies, behavioral research, or data collection operations in an academic or industry setting.
• Track record of partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications.
• 10 years of experience in user research operations, data collection coordination, or a related technical operations role.
• Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices.
• Experience working directly with engineering and science teams, with comfort reading technical documentation, data schemas, or experiment specifications.
• Familiarity with handling sensitive human data and adhering to strict privacy and consent protocols.
• Highly organized self-starter who can manage multiple concurrent internal studies with minimal oversight.
• Strong interpersonal and written communication skills, with the ability to collaborate fluidly across both technical and non-technical stakeholders.
• Strong attention to detail with the ability to identify data anomalies and inconsistencies during live collection.

Responsibilities

• Plan, 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 improvements

What This Job Offers

• Job Type: Full-time
• Career Level: Senior