The Machine Learning Engineer will join the Search team for Video catalog within the Apple Services Engineering AI/ML organization. This role focuses on developing scalable systems and machine learning models that enhance search relevance and personalization across Apple platforms. The team values innovation and craftsmanship, working collaboratively to translate advanced machine learning research into production features. The engineer will design and deploy large-scale ML systems while ensuring user privacy and delivering delightful experiences to millions of users.

• Experience in machine learning, natural language processing, information retrieval, or large language models.
• Strong programming skills in Python, Java, and Go.
• Hands-on expertise in ML libraries such as PyTorch, JAX, and TensorFlow.
• In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking.
• Bachelor's degree or higher in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.

• Design and deploy large-scale machine learning systems for search and discovery.
• Apply machine learning and natural language understanding to model user intent.
• Build and optimize data processing, ML models, retrieval pipelines, and ranking systems.
• Collaborate closely with cross-functional teams to bring advanced ML technologies into production.
• Translate product goals into technical solutions that improve user experience.

• 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.