ML Data Operations Engineer

Quick Facts

• Role: ML Data Operations Engineer

Description

Apple’s ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering next-generation consumer machine learning features. In this role, you will work closely with Apple scientists and engineers, with hands-on responsibility for bring-up, execution, and quality oversight of internal data collection studies. You’ll develop a technical understanding of the ML experiments you support and operate in a highly collaborative, cross-functional environment.

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, and evaluation criteria
• Bring up and maintain pre-release hardware and software platforms for data collection; troubleshoot and triage to minimize disruptions
• Create and maintain technical documentation for platform setup, study protocols, and data handling procedures
• Manage day-to-day logistics: schedule participants, configure setups, and maintain smooth study session flow
• Collaborate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements
• Track and communicate study progress, blockers, participant throughput, and dataset status to 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
• Track record partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications

Benefits

Join a collaborative, technically demanding environment working with scientists and engineers to deliver consumer machine learning features.