The Machine Learning Engineer will be part of Apple's Video Computer Vision Face and Body technologies team, focusing on developing ML models for computer vision and graphics applications. This role involves engaging in the entire ML cycle, from data collection to model validation. The team aims to solve complex challenges in human representation and motion, impacting millions of users. Collaboration with other ML engineers and multi-functional teams is essential to deliver high-quality features on visionOS and iOS platforms.

• BS degree and 10+ years of experience in a relevant field
• MS degree in computer vision, computer graphics, machine learning or related field
• PhD in computer vision, computer graphics, machine learning, computer science, computer engineering or related fields
• Proficiency in Python and software engineering skills
• Experience with PyTorch
• Excellent communication skills and experience working with multi-functional teams
• Independent problem-solving skills
• Self-motivated with a proven track record of prioritizing and delivering tasks on schedule

• Develop ML models for computer vision and graphics applications
• Engage in the entire ML cycle from data collection to model validation
• Collaborate closely with other ML engineers and data/software engineers
• Adapt state-of-the-art methods or implement new methods for visionOS and iOS platforms
• Deliver high-quality features to diverse end-users

• 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.