Machine Learning Engineer - AI & ML Evaluation Frameworks
Apple · Cupertino ·
- Category
- ML ai
- Experience
- 3+ years
- Company size
- 1000+
Apple · Cupertino ·
The Health Sensing Machine Learning Interpretability & Analytics (MLIA) team ensures clinical rigor and contextual trust are at the foundation of Apple’s health sensing features. We are looking for an exceptional ML Engineer to help us build the next generation of scalable evaluation infrastructure and lead rigorous investigations into model performance. You will develop cutting-edge tools, synthetic data pipelines, and automated frameworks that ensure our health features are mathematically sound, demographically equitable, and clinically safe. If you are passionate about AI safety, robust software architecture, and pushing the boundaries of ML innovation, come join us!
In this role, you will architect and build large-scale evaluation frameworks to interrogate unimodal ML systems and multi-modal foundation models. Beyond infrastructure, you will lead deep-dive ML evaluations, performing failure analysis to uncover performance gaps, reasoning flaws, and edge cases. You will translate findings into actionable insights and work directly with algorithm teams to improve the safety and reliability of our health features. Your work will empower teams across Apple to rapidly evaluate multi-modal sensor fusion while upholding Apple's privacy standards.