ML Data Operations Engineer

Apple•Washington, DC

About The Position

Apple's ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts that power next-generation consumer machine learning features. The role works closely with Apple scientists and engineers, developing a technical understanding of the ML experiments being supported in addition to coordinating logistics. The engineer is responsible for the hands-on bring-up, execution, and quality oversight of internal data collection studies in a collaborative, technically demanding, cross-functional environment.

Requirements

  • Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, or Operations, or an 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.

Nice To Haves

  • 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, and 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 able to manage multiple concurrent internal studies with minimal oversight.
  • Strong interpersonal and written communication skills, with the ability to collaborate across technical and non-technical stakeholders.
  • Strong attention to detail and ability to identify data anomalies and inconsistencies during live collection.

Responsibilities

  • Support internal data collection efforts for consumer machine learning features.
  • Work closely with Apple scientists and engineers and develop a technical understanding of the ML experiments being supported.
  • Bring up and execute internal data collection studies.
  • Oversee the quality of data collection studies.
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