The Staff/Senior Machine Learning Engineer will be part of the Information Intelligence team at Apple, focusing on developing advanced Search and Question Answering experiences using cutting-edge technologies. This role involves leveraging machine learning and deep learning techniques to enhance how users access information across various Apple products. The team is diverse, comprising applied scientists and engineers, and is dedicated to pushing the boundaries of search technologies. The engineer will work with large datasets and collaborate with experts to improve query understanding and ranking.

• MS in Computer Science or related field
• 10+ years of work experience in machine learning, deep learning or related field
• 10+ years experience in shipping Search and Q&A technologies and ML systems
• Excellent programming skills in mainstream programming languages such as C++, Python, Scala, and Go
• Experience delivering tooling and frameworks to evaluate individual components and end-to-end quality
• Strong analytical skills to systematically identify opportunities to improve search relevance and answer accuracy
• Strong written and verbal communication with the ability to articulate complex topics
• Excellent interpersonal skills and teamwork; demonstrated ability to connect and collaborate with others
• Passion for building phenomenal products and curiosity to learn
• PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
• Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering)
• Strong and validated experience of ML development and production systems
• Experience working with foundation models and LLMs

• Develop world-class Search and Q&A experiences for Apple customers using advanced search technologies and large language models.
• Collaborate with Search and AI engineers on large scale machine learning projects to improve Query Understanding, Retrieval, and Ranking.
• Push the boundaries on document retrieval and ranking by developing sophisticated machine learning models.
• Utilize embeddings and deep learning techniques to assess the quality of matches.
• Implement online learning to adapt quickly to changes in user queries.
• Combine information from structured and unstructured sources to deliver accurate answers.
• Train, fine-tune, and deploy machine learning models at scale using the latest advances in online inference optimization.

• 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.