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At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, smart people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product.\nDo 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.\nDescription\nApple'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\nMinimum Qualifications\nBachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience.\nExperience supporting or executing human user studies, behavioral research, or data collection operations in an academic or industry setting.\nTrack record of partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications.\nPreferred Qualifications\n10 years of experience in user research operations, data collection coordination, or a related technical operations role.\nHands-on familiarity with ML data pipelines, annotation tools, or dataset management practices.\nExperience working directly with engineering and science teams, with comfort reading 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