The role of Machine Learning Engineer at Apple focuses on enhancing the safety and inclusivity of generative AI applications. The team is dedicated to exploring innovative solutions in machine learning, particularly with large language models and multimodal systems. As part of Apple's Responsible AI group, the engineer will work on evaluating and improving generative AI features. This position emphasizes applied data science, collaboration, and the development of evaluation methodologies.

• MS or PhD in Computer Science, Machine Learning, Statistics, or related fields.
• Experience working with generative models for evaluation and product development.
• Strong engineering skills and experience in writing production-quality code in Python.
• Deep experience in foundation model-based AI programming.
• Experience working with noisy, crowd-based data labels and human evaluations.
• Experience working in the Responsible AI space.
• Prior scientific research and publication experience.
• Strong organizational and operational skills.

• Develop and conduct evaluations of the safety of Apple Intelligence features.
• Research and develop auto-grading methodology and infrastructure.
• Produce safety evaluations that align with Apple's Responsible AI values.
• Perform thoughtful data sampling, creation, and curation for evaluation datasets.
• Provide high quality, detailed annotations and careful auto-grading.
• Analyze evaluation results to understand their implications for 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.