
Senior Exercise Physiologist - Health AIML
Required skills
- machine learning
- health science
- exercise physiology
- physical activity
- human performance
- athletic training
- rehabilitation
- clinical care
- product development
- written standards
Nice to have
- ML systems
- model outputs
- Python for data analysis
- behavior change research
- adherence
- long-term engagement
Role summary
Apple's Health AI team seeks a Senior Exercise Physiologist to define and measure evidence-based guidance for physical activity, training, recovery, and aging. This role involves translating exercise physiology and research into actionable insights for machine learning engineers and data scientists. Key responsibilities include developing standards, creating evaluations, reviewing model outputs, and ensuring content quality at scale. The position requires direct experience with data analysis, Python scripting, and working within code repositories, with a strong emphasis on applying scientific evidence over enthusiasm. Collaboration with cross-functional teams is essential.
Description
In this role, you will use your background in exercise physiology to define what good, evidence-based guidance about physical activity looks like at Apple, and to make that definition measurable. Evaluation is the core of the work. You will write the standards our health and fitness work is held to, turn those into evaluations, review model outputs, and adjudicate when needed. Physical activity is one of the most powerful levers on long-term health and one of the least well served by the way health information usually reaches people, and this role exists to close that gap with evidence rather than enthusiasm. The role requires close collaboration with machine learning engineers, data scientists, and clinicians, and regular translation of physiology and research evidence into terms they can act on.
Minimum Qualifications
10+ years of experience applying exercise, physical activity, or human performance evidence with people, through coaching, athletic training, rehabilitation, clinical care, research, or product development. Experience turning research evidence into written standards, guidelines, rubrics, or evaluation criteria. Experience judging the quality of generated content against an explicit standard, at volume, and turning what you found into specific changes. Experience working directly in code and data, including running Python scripts or notebooks to examine data and evaluation results, and working in a shared code repository. MS or Ph.D. in Exercise Physiology, Exercise Science, Kinesiology, Sports Science, or a related field (or equivalent qualification). An active clinical license (MD or DO, DPT, RD, NP, or PA) with equivalent depth in exercise and physical activity is also accepted.
Preferred Qualifications
Experience defining quality, safety, or evaluation criteria for machine learning systems, including reading model outputs directly and working with engineers on how those criteria are scored. Experience writing code to analyze data or evaluation results, for example Python for data analysis, or adding evaluation criteria directly to a codebase. Ph.D. in Exercise Physiology, Sports Science, Kinesiology, or a related field. Experience applying exercise and physical activity guidance across more than one population, for example athletic, military, general adult, older adult, or clinical populations. Experience with behavior change research, including how adherence and long-term engagement are measured over months and years.
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