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ML Data Operations Engineer

Apple· Hardware
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Hybrid (San Diego, CA)$142.3k - $214.3kPosted 4w ago

About the role

Apple ML Data Operations engineer to support internal data collection efforts for next-generation consumer ML features. Roles include hands-on bring-up, execution, and quality oversight of internal data collection studies, collaborating with researchers, engineers, and scientists, and developing technical understanding of ML experiments supported.

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

Qualifications

  • 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.
  • 3+ 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.

Skills

Required:ML data collection coordinationTechnical documentationCross-functional collaborationPrivacy and data handling

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • a range of discounted products and free services
  • reimbursement for certain educational expenses — including tuition
  • discretionary bonuses or commission payments as well as relocation (may be eligible)
  • Apple shareholder participation through stock programs
  • Employee Stock Purchase Plan
Last updated Sep 25, 2026. Interested? Apply on the company site.

About Apple

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