Apple is seeking a Machine Learning Engineer to help build the next generation of intelligent search and AI experiences that understand user intent, context, and personal information while preserving privacy. In this role, you will work with large language models, semantic retrieval systems, ranking models, and retrieval-augmented generation to design, optimize, and deploy relevant, personalized, and context-aware experiences across Apple's ecosystem. You will build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems that improve search quality and AI-powered experiences. You will improve the underlying software infrastructure, optimize solutions for low-latency inference, and adapt large foundation models into smaller, highly capable models that operate efficiently under on-device memory, compute, power, and latency constraints. Minimum qualifications include a Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with experience in machine learning, deep learning, natural language processing, information retrieval, search, recommender systems, or generative AI. Proficiency in Python and/or C/C++, and experience building production-quality software using modern machine learning frameworks such as PyTorch, JAX, or TensorFlow. Preferred qualifications include a Master's or PhD in a related field, experience building and deploying semantic search, retrieval, or ranking systems at scale in production environments, hands-on experience with retrieval-augmented generation, dense retrieval, or neural

Apple is seeking a Machine Learning Engineer to help build the next generation of intelligent search and AI experiences that understand user intent, context, and personal information while preserving privacy. In this role, you will work with large language models, semantic retrieval systems, ranking models, and retrieval-augmented generation to design, optimize, and deploy relevant, personalized, and context-aware experiences across Apple's ecosystem. You will build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems that improve search quality and AI-powered experiences. You will improve the underlying software infrastructure, optimize solutions for low-latency inference, and adapt large foundation models into smaller, highly capable models that operate efficiently under on-device memory, compute, power, and latency constraints. Minimum qualifications include a Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with experience in machine learning, deep learning, natural language processing, information retrieval, search, recommender systems, or generative AI. Proficiency in Python and/or C/C++, and experience building production-quality software using modern machine learning frameworks such as PyTorch, JAX, or TensorFlow. Preferred qualifications include a Master's or PhD in a related field, experience building and deploying semantic search, retrieval, or ranking systems at scale in production environments, hands-on experience with retrieval-augmented generation, dense retrieval, or neural