Staff Machine Learning Engineer - Tools & Frameworks AI
Apple - Cupertino, United States of America
Posted Mar 12, 2026
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
- Not verified
- Verification
- Not verified last checked Jun 13, 2026
- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 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
Staff Machine Learning Engineer - Tools & Frameworks AI Cupertino, United States of America Our team of applied ML scientists and engineers works to enhance the experience and productivity of software development at Apple. Our team applies state-of-the-art ML models to solve real-world problems in software quality and development workflows. We're looking for talented and enthusiastic team members to join us in our efforts. If this sounds like you, we have many challenging and interesting problems to work on together and would love to talk to you! Our team designs and builds ML solutions to transform how Apple and developers in the ecosystem approach developing quality software at scale. We are a team of applied scientists, infrastructure engineers, and machine learning engineers who work with NLP, computer vision, and multimodal domains to create AI-powered testing solutions. In this role, you will be responsible for developing novel ML approaches to challenging quality problems at scale. You'll work hands-on with a diverse set of ML techniques to find what actually works in production. You'll guide technical direction for the team, mentoring junior engineers while maintaining deep involvement in the code and experimentation yourself. Your technical judgment and understanding of both generative models and traditional ML methods will directly shape our product direction. You will be successful and feel fulfilled in our team if you enjoy tackling challenging problems with creative solutions, have strong intuition for what will and won't work in practice, and thrive in a collaborative team setting where you can
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