ML Data Operations Engineer

Quick Facts

• Role: ML Data Operations Engineer

• Focus: Internal ML data collection operations supporting consumer machine learning features

Description

Apple is seeking an ML Data Operations Engineer to support internal data collection efforts that power next-generation consumer machine learning features. You will plan, execute, and oversee the bring-up and quality of internal data collection studies in a collaborative, cross-functional environment with ML scientists and engineers.

Responsibilities

• Plan, execute, and track internal ML data collection studies with researchers, engineers, and scientists

• Develop understanding of supported ML experiments (model objectives, data requirements, labeling, evaluation criteria) to ensure dataset quality

• Bring up and maintain pre-release hardware and software platforms; troubleshoot and triage issues to minimize study disruption

• Create and maintain technical documentation for platform setup, study protocols, and data handling procedures

• Manage day-to-day logistics of study sessions (scheduling participants, configuring setups, maintaining smooth session flow)

• Collaborate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements before and during execution

• Track and communicate progress, blockers, participant throughput, and dataset status to cross-functional partners and stakeholders

• Identify workflow gaps and define, document, and socialize process improvements

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 partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications

Benefits

• Opportunity to work on internal data collection studies that directly support next-generation consumer machine learning features

• Highly collaborative, technically demanding role working closely with scientists and engineers