The Machine Learning Engineer will be part of the Multimodal Intelligence team at Apple, focusing on building the infrastructure and production systems that enable multimodal foundation models to deliver innovative features. This role involves end-to-end model delivery, including data curation, training pipelines, and evaluation for on-device applications. The team aims to create experiences where devices can understand and interact with the world around them. Collaboration with various engineering teams is essential to align with future hardware and product needs.

• Experience in deep learning with demonstrated work in at least one area of multimodal systems.
• Proficiency in Python and in a modern deep learning framework such as PyTorch or JAX.
• Experience with rapid prototyping, reproduction, and validation of research ideas.
• Ability to work in a collaborative environment.
• Ability to communicate the results of analyses in a clear and effective manner.
• BS and a minimum of 3 years of relevant industry experience.
• Master's or PhD, or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or a related technical field.
• Deep expertise in multimodal foundation models, with a focus on practical applications.
• Track record of translating research into practical applications either through published work or industry experience.
• Strong applied research experience in at least one major area of model development, particularly as it applies to multimodal systems.
• Experience with large-scale training pipelines, including working with large datasets and scaling models across distributed systems.
• Experience bridging research ideas with production constraints.

• Build and scale data curation and training pipelines for multimodal models.
• Fine-tune and optimize large multimodal models for on-device and hybrid execution.
• Establish reproducible evaluation and regression testing for text and visual understanding.
• Harden promising approaches into robust, maintainable production systems under real constraints.
• Collaborate with modeling, platform, hardware, and product engineering teams to align implementation decisions with future needs.

• 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.