AIML - Sr Machine Learning Engineer - Answers, Knowledge & Information (AKI)
Apple - Cupertino, United States of America
Posted Aug 8, 2025
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- 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
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
AIML - Sr Machine Learning Engineer - Answers, Knowledge & Information (AKI) Cupertino, United States of America The Answers, Knowledge and Information team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we're pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple's most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more. Join us in shaping the future of how the world connects with information! We are looking for a senior Machine Learning Engineer with a passion for building scalable, high quality solutions to evaluate personalized search applications. In this role, will directly impact how we assess and improve the quality of novel search applications by driving solutions for data generation, data quality assessment, offline and online metrics, and methods for statistical model and search quality assessment. Your work will impact the quality of innovative Search experiences across Apple products. In this role you will have the opportunity to develop data generation methodologies for personalized model and search systems evaluations, online and offline metrics for quality assessment and build scalable systems for comprehensive evaluation. Our team is responsible for models and evaluation of search experiences that answer user's questions using their personal documents with privacy at the forefront. Role responsibilities include: - Design and implement novel data generation and data
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