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1–2 jobs· newest first

ML Data Operations EngineerNew
Apple · Philadelphia, US
On-site
ML Data Operations EngineerNew
Apple · Washington DC, US
On-site

+10K new in the last hour

ML Data Operations Engineer

Apple · Posted Nov 11, 2026

Philadelphia, Pennsylvania, United States
On-site

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Support internal data collection efforts powering next‑generation consumer machine learning features.

Responsibilities

Develop technical understanding of ML experiments
Bring‑up, execute, and oversee internal data collection studies
Collaborate with Apple scientists and engineers
Define data requirements, quality standards, and collection specifications

Requirements

Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent
Nice to have: user research operations
Nice to have: technical operations
Nice to have: experience with engineering and science teams
Nice to have: handling sensitive human data

Skills

data collection operations ML data pipelines annotation tools dataset management privacy and consent protocols data schemas

See full job description

ML Data Operations Engineer

Apple · Posted Nov 10, 2026

Washington DC, District of Columbia, United States
On-site

Apply with RefersoAI Apply on careers page

Support internal data collection efforts powering Apple’s next generation of consumer machine learning features.

Responsibilities

Develop technical understanding of ML experiments
Bring-up, execute, and oversee internal data collection studies
Collaborate with Apple scientists and engineers
Define data requirements, quality standards, and collection specifications

Requirements

Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent
Nice to have: 3 years of experience in user research operations or related technical operations
Nice to have: familiarity with ML data pipelines
Nice to have: annotation tools
Nice to have: dataset management practices

Skills

supporting or executing human user studies data collection operations partnering with ML engineers or researchers defining data requirements quality standards

collection specifications

reading technical documentation

experiment specifications

handling sensitive human data

adhering to privacy and consent protocols

annotation tools

See full job description