The Machine Learning Engineer will play a crucial role in the evolution of Apple Maps, focusing on innovative ways for users to discover information. This position involves leveraging Machine Learning and Generative AI to enhance search quality within the Maps application. The team is dedicated to building groundbreaking technologies that impact millions of users daily. Candidates will have the opportunity to work independently and collaboratively in a dynamic environment.

• MS or Ph.D. in computer science or a related field with 2+ years of industry experience
• Proven record in delivering end-user facing Machine Learning driven products
• Strong programming experience in Java, C++, or Python
• Knowledge and experience with Tensorflow, Pytorch, or Jax frameworks
• Excellent interpersonal and communication skills
• Attention to detail, data accuracy, and quality of output
• Expertise in machine learning and natural language processing techniques
• Practical understanding of the mathematics behind modern machine learning
• Good knowledge of big data processing with experience in Hadoop, Spark, or Hive

• Develop and implement Machine Learning models to improve search quality in Apple Maps
• Collaborate with team members to design innovative solutions for user discovery
• Utilize Generative AI techniques to enhance user experience
• Ensure high standards of data accuracy and quality in outputs
• Stay updated with emerging technologies and techniques in Maps technology

• 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.