The role involves working as a Machine Learning Engineer at Apple, focusing on the development and evaluation of generative AI applications. The team is dedicated to enhancing the safety and inclusivity of Apple's AI-powered features. Responsibilities include tackling innovative problems related to large language models and multimodal applications. The position emphasizes applied data science and collaboration across diverse teams to ensure responsible AI practices.

• 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.

• Assess, quantify, and improve the safety and inclusivity of generative AI features.
• Develop and carry out evaluations of Apple Intelligence features.
• Research and develop auto-grading methodology and infrastructure.
• Produce safety evaluations that align with Apple's Responsible AI values.
• Conduct thoughtful data sampling, creation, and curation for evaluation datasets.
• 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.