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Do you love working on challenges that no one has solved yet? As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple's customers every single day.
Description
Apple's ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering our next generation of consumer machine learning features. In this role, you will work shoulder-to-shoulder with full-time Apple scientists and engineers, not just coordinating logistics, but developing a genuine technical understanding of the ML experiments you support. You will be responsible for the hands-on bring-up, execution, and quality oversight of internal data collection studies, operating in a highly collaborative and technically demanding cross-functional environment
Minimum 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.
Preferred Qualifications
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: eee1100075e2780cfb48c8b56ece1b9e
- Posted 1 day ago
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