As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will contribute to innovative ML features at Apple. The role emphasizes shipping ML-based products and involves working on the entire ML development pipeline. You will collaborate with ML researchers and engineers to build production-quality software and integrate models into Apple's infrastructure. The ideal candidate is self-driven, willing to iterate on ideas, and has a strong foundation in machine learning.

• BS or MS with 3-5 years of ML software engineering experience or a PhD in Computer Science, Computer Engineering, or relevant fields.
• Strong foundation in classical ML models, deep neural networks, and multimodal foundation models.
• Experience in building model training and evaluation pipelines in Python and PyTorch.
• Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or TensorFlow.
• Experience in on-device ML model deployment and optimization.
• Proficient in Swift, Objective C, C++, or Go.

• Develop and optimize ML training pipelines and runtime inference infrastructure.
• Collaborate closely with ML researchers, software, firmware, and operation/data engineers.
• Deliver the necessary pipeline for model development and evaluation.
• Build production software to integrate models and related functionalities within Apple's software infrastructure.
• Prototype and iterate on creative approaches to datasets and model training.

• 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.