The Machine Learning Engineer role at Apple Maps focuses on enhancing search quality through innovative machine learning and generative AI techniques. The team aims to elevate the intelligence and accuracy of Apple Maps, impacting millions of users globally. Engineers will work on various projects related to query understanding, intent modeling, and ranking. This position offers a unique opportunity to blend science and engineering while mentoring aspiring applied scientists and engineers.

• Ph.D in computer science or equivalent field with 7+ years of industry experience.
• Expertise in machine learning and natural language processing, including classification and feature engineering.
• Practical understanding of the mathematics behind modern machine learning, linear algebra, and statistics.
• Good knowledge of big data processing with experience in Hadoop, Spark, or Hive.
• Proven expertise in applying Generative AI and Large Language Models to search or NLP tasks.
• Prior experience in a consumer-facing product is desired.
• Prior team lead experience is desired.

• Develop and optimize machine learning algorithms for local search issues.
• Design and develop tools and processes for backend data-extraction pipelines.
• Collaborate with various teams to develop features that enhance search experiences.
• Perform hands-on analyses to address complex hypotheses and questions.
• Mentor aspiring applied scientists and engineers to expand their impact.

• 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.