The role is for a machine learning engineer within the Apple Ads Machine Learning Platform team, focusing on building and scaling innovative ML systems for optimized advertising content. The team emphasizes reliability, simplicity, and scalability while working closely with ML engineers and scientists. The engineer will design secure and scalable back-end systems and contribute to the development of machine learning products that align with Apple's privacy commitments. This position requires a results-oriented individual who thrives in a fast-paced environment and is passionate about improving the developer experience for AI/ML practitioners.

• Experience writing mission-critical code for production machine learning systems
• Experience building ML infrastructure, frameworks, or services used by multiple teams
• Experience building SDKs, APIs, and automation UIs used by development teams
• Proven experience building automation and CI/CD
• 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
• Prior experience applying ML at scale in advertising, recommender systems, information retrieval, or related domains
• Experience with distributed training and/or optimizing large-scale models for low-latency serving
• Experience building infrastructure for diverse sets of model development use cases including LLMs, multimodal models, classical ML, and reinforcement learning
• Experience with agentic AI
• Prior experience in privacy-preserving ML
• PhD in Computer Science or related field with 3+ years of engineering experience and 5+ years of machine learning experience; or MS in Computer Science or related field with 6+ years of engineering experience and 5+ years of machine learning experience; or BS in Computer Science or related field with 7+ years of engineering experience and 5+ years of machine learning experience

• Design and develop secure and scalable back-end systems for machine learning applications
• Collaborate with ML engineers and scientists to enhance ML features, models, and applications
• Build high-performing systems from the ground up in partnership with various teams
• Select appropriate technologies and solutions for unique ad network challenges
• Contribute to the development of machine learning products that uphold Apple's privacy commitments
• Support scalable modeling and continuous experimentation by all Ads teams

• 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.