The Machine Learning Engineer role at Apple focuses on innovating and applying state-of-the-art research in machine learning to address complex data challenges. The position is part of the Data and Machine Learning Innovation team, which aims to develop transformative products and enhance Apple Intelligence. The engineer will collaborate with a multidisciplinary team to design and implement data generation frameworks and evaluation pipelines. This role also offers opportunities for publishing and presenting groundbreaking research at academic venues.

• 3+ years of experience with developing and evaluating ML applications.
• Demonstrated expertise in computer vision, natural language processing, and machine learning.
• Deep understanding of multi-modal foundation models.
• Strong programming skills and hands-on experience using Python, PyTorch, or Jax.
• Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas.

• Innovate and apply state-of-the-art research in machine learning to tackle complex data problems.
• Design and develop a comprehensive data generation and curation framework for Apple Intelligence foundation models.
• Build robust model evaluation pipelines for continuous improvement of Apple Intelligence foundation models.
• Participate in data-model co-design and co-develop practices with a multidisciplinary team.
• Showcase research work by publishing and presenting at premier academic venues.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.