The role is for an engineer on the Apple Ads Machine Learning Platform team, focused on building and scaling innovative machine learning systems for optimized advertising content. The team aims to empower Ads teams while ensuring user privacy and delivering high-quality experiences. The engineer will collaborate closely with ML engineers and scientists to develop secure and scalable back-end systems. This position requires a results-oriented individual who thrives in a fast-paced environment and is passionate about building high-performing systems.

• Experience writing mission-critical code for production machine learning systems
• Experience building ML infrastructure, frameworks or services used by multiple teams
• Solid understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing
• Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow
• Strong data modeling and data architecture skills, with a high bar for system and data quality

• Design and develop secure and scalable back-end systems for machine learning products
• Collaborate with various teams to build high-performing, elegant systems from the ground up
• Select appropriate technologies and build solutions for unique ad network challenges
• Contribute to a culture that emphasizes reliability, simplicity, and scalability
• Build production data pipelines for ML systems where scale and performance are critical

• 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.