Apple Ads is seeking a highly skilled Machine Learning Engineer to join the Predictions group, focusing on developing core machine learning models for ad predictions and monetization across Apple’s platforms. The ideal candidate will have deep expertise in machine learning and thrive in a fast-paced, privacy-first environment. This role involves working with applied ML, deep learning, and retrieval systems to optimize user interactions and marketplace outcomes. The engineer will also explore emerging techniques in Large Language Models and Reinforcement Learning to enhance Apple's ad prediction systems.

• 6+ years of experience applying machine learning and statistical modeling at scale, preferably in ad tech, recommender systems, or web-scale search/retrieval.
• Deep experience with neural network architectures such as Transformers, DNNs, and RNNs, along with training pipelines using TensorFlow or PyTorch.
• Practical understanding of reinforcement learning, explore/exploit strategies, and bandit-based optimization.
• Experience working with high-volume data pipelines, A/B testing infrastructure, and performance measurement at scale.
• Proficient in Python and familiar with SQL, Scala, or Java for production environments.
• Bachelor's or equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.
• MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.

• Develop machine learning models that predict user interaction and optimize marketplace outcomes.
• Work at the intersection of applied ML, deep learning, and retrieval systems.
• Explore and operationalize emerging techniques in Large Language Models and Reinforcement Learning.
• Translate abstract ideas into concrete, high-impact solutions.

• 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.