The Health Sensing Machine Learning Interpretability & Analytics (MLIA) team at Apple is seeking an exceptional ML Engineer to develop scalable evaluation infrastructure and lead investigations into model performance. The role focuses on building tools, synthetic data pipelines, and automated frameworks to ensure health features are mathematically sound and clinically safe. The engineer will work on both unimodal and multi-modal ML systems, performing failure analysis and translating findings into actionable insights. This position is ideal for those passionate about AI safety and robust software architecture.

• BS in Computer Science, Machine Learning, Statistics, or a related field
• 3+ years of experience in ML Engineering or Applied ML
• Strong experience in evaluating supervised, unsupervised, LLMs, and deep learning models
• Proficiency in Python with the ability to write production-grade code
• Hands-on experience in failure analysis and evaluating LLMs
• Experience building data pipelines and automated evaluation systems
• Strong communication skills to articulate complex technical concepts

• Architect and build large-scale evaluation frameworks for ML systems
• Lead deep-dive ML evaluations and perform failure analysis
• Translate findings into actionable insights for algorithm teams
• Empower teams across Apple to evaluate multi-modal sensor fusion
• Uphold Apple's privacy standards in all evaluations

• 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.