The Health AIML team at Apple is seeking a Machine Learning Research Scientist who is dedicated to solving real-world health and fitness problems. This role involves developing next-generation multimodal models to enhance intelligent health experiences for millions of users. The ideal candidate will have strong expertise in large multimodal models and will work at the intersection of AI and health. This position offers the opportunity to shape the future of health and fitness technologies at Apple.

• PhD in Computer Science, Engineering, Machine Learning, Statistics, Mathematics, or a related field.
• Industry work experience.
• Experience contributing to major LLM training runs.
• Proven track record of publishing state-of-the-art research.
• Strong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.
• Experience in training and evaluating multimodal models.
• Understanding of time-series modeling, self-supervised learning, and cross-modal training.
• Ability to evaluate and improve deep learning architectures independently.
• Motivated by safely deploying LLMs in the health and fitness domain.

• Lead the development of foundational technology for understanding health and fitness data.
• Guide multimodality research within the team.
• Develop innovative technologies that impact users' health and fitness.
• Collaborate with research scientists and engineers to deliver impactful solutions.
• Shape the future of health and fitness technologies at Apple.

• 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.