The Senior Machine Learning Engineer at Apple will focus on building the next generation of intelligent search and AI experiences. This role involves working with large language models and semantic retrieval systems to enhance user intent understanding while maintaining privacy. The engineer will optimize solutions for low-latency inference and adapt large models for efficient on-device operation. Collaboration with cross-functional teams is essential to deliver AI-powered features across Apple's ecosystem.

• Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Background in machine learning, deep learning, natural language processing, information retrieval, search, recommender systems, or generative AI.
• Experience with semantic retrieval, embedding models, reranking, or retrieval-augmented generation systems.
• Programming skills in Python and/or C/C++, with experience using modern machine learning frameworks such as PyTorch, JAX, or TensorFlow.
• Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Experience building and deploying semantic search, retrieval, or ranking systems at scale in a production environment.
• Hands-on experience with retrieval-augmented generation, dense retrieval, or neural reranking pipelines.
• Experience adapting or distilling large foundation models into compact, efficient models for on-device deployment.
• Familiarity with model optimization techniques such as quantization, pruning, or knowledge distillation.
• Experience designing and running offline evaluations and online experiments (A/B testing) to measure search quality, ranking, or model performance.
• Strong understanding of query understanding, intent modeling, or personalization in search or recommendation systems.
• Experience working across cross-functional teams to ship AI-powered features in consumer products.

• Design, optimize, and deploy relevant, personalized, and context-aware experiences across Apple's ecosystem.
• Build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems to improve search quality.
• Enhance the underlying software infrastructure for low-latency inference.
• Adapt large foundation models into smaller, efficient models for on-device deployment.
• Collaborate with cross-functional teams to deliver AI-powered features in consumer 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.