The role is for a versatile Machine Learning Software Engineer focused on developing innovative, ML-driven product features for Apple Watch and other devices. The team collaborates with various research and product teams at Apple to create high-impact features that enhance human-computer interaction. The engineer will work on everything from training advanced models to rapid on-device prototyping and full-scale productization. This position requires a passion for pushing the boundaries of sensing technology and improving user experiences.

• M.S. or Ph.D. in Computer Science, Machine Learning, or a related field.
• Proficiency with Swift or Objective-C and developing on Apple platforms.
• Experience using Python and deep learning frameworks such as PyTorch or TensorFlow for predictive modeling.
• Excellent communication and collaboration skills, with the ability to work independently or in small teams.
• Experience optimizing and profiling applications for performance and power consumption.

• Develop innovative, ML-driven product features for Apple Watch and other devices.
• Collaborate with cross-functional partners across Apple to explore novel experiences.
• Work within the full ML development cycle, including data collection, model training, and optimization.
• Define metrics, evaluate models, perform failure analysis, and deploy models to resource-constrained devices.
• Prototype new experiences and contribute to the development and shipping of products.

• 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.