AIML - Research Scientist, Health

Apple seeks a Senior Research Scientist in Health for its PAIS team in Zürich. The role focuses on developing machine learning methodologies for health applications using deep learning and statistical rigor.

This position sits within the Personalized AI for Science (PAIS) team, which drives research into machine learning and health science. The team develops new statistical and ML methods for Apple’s health and wellbeing apps, creating features that impact a billion devices globally. The role involves incubating ambitious research ideas and translating clinical questions into technical solutions.

Responsibilities

• Design, train, and adapt modern deep learning models and architectures using large-scale physiological and behavioral data.
• Apply statistical expertise to rigorously evaluate models, including subgroup analyses and robustness to distributional shifts.
• Characterize model failure modes and ensure defensible conclusions are drawn from observational health data.
• Translate clinical and product requirements into well-defined problem statements.
• Engage with the academic community through publications and presentations.
• Collaborate with product teams to transition research findings into deployed health features.

Requirements

• Proven experience designing and training modern deep learning models, including foundation models, self-supervised pretraining, multimodality, and parameter-efficient adaptation.
• Strong background in statistics with the ability to draw robust conclusions from observational data.
• Experience in characterizing and improving model robustness under distributional shifts typical in health data.
• Ability to design and execute complex model evaluations beyond standard validation protocols.

Nice to have

• Proficiency in Python and modern ML/analysis stacks, including LLM-based coding and analysis.
• Excellent communication skills, with the ability to present technical work to clinical and broad technical audiences.
• Research or applied experience in deep learning and statistical modeling within the health domain.
• Experience with causal inference, survival analysis, time-series modeling, or longitudinal analysis.
• Experience with rigorous evaluation methodology for ML in clinical or scientific settings.
• Publications at top-tier venues such as NeurIPS, ICML, or ICLR.

About the company

The PAIS team is a close-knit group of deeply technical AI and ML research scientists. They are passionate about model robustness and maintaining high standards of scientific rigor in their work.

• Close-knit team of deeply technical AI/ML research scientists.
• Strong focus on model robustness and scientific rigor.