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AIML - Staff Machine Learning Engineer

Apple - Cary, United States of America

Posted Oct 13, 2025

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Salary
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401(k) match
Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Schedule

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Application

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About this role

AIML - Staff Machine Learning Engineer Cary, United States of America Would you like to play a part in the next revolution in human-computer interaction? Come build the future with the Apple Knowledge & Information team. Help lead the creation of a truly personalized user experience, one that adapts to the unique needs and habits of each individual. The Apple Knowledge & Information (AKI) Entity Resolution team is looking for senior and staff engineers to lead software projects suffusing knowledge of the user throughout Apple's products. Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more. You will be a hands on, technical leader as your team partners with a variety of subject matter experts to design, build, and integrate their components into a seamless platform for creating personalized Siri experiences that surprise and delight. Engage with leaders and cross-functional partners to define requirements Partner with application developers to build personalized features users love Build entity resolution APIs that Siri application developers love Lead highly cross-functional software projects Mentor junior software engineers Partner with application owners on API design, implementation, and integration Validate new platform features by leading early adoption Minimum Qualifications: 8 years of professional software experience BS in computer science or related fields Experience leading software engineering teams and / or projects Experience designing and shipping novel systems architectures Passion for great products Exceptional software engineering skills Ability to identify similar

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