Senior Exercise Physiologist - Health AIML

Apple
Cupertino, United States of America2026-09-17

About the job

The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit, interdisciplinary team of research scientists, machine learning engineers, clinicians, and health scientists working on technologies that reach millions of people. We are looking for a senior exercise physiologist who wants to shape what people are told about how to move, train, recover, and stay capable as they age.

Responsibilities

- Define what good, evidence-based guidance about physical activity looks like at Apple, and make that definition measurable

- Write the standards our health and fitness work is held to and turn those into evaluations

- Review model outputs and adjudicate when needed

- Collaborate closely with machine learning engineers, data scientists, and clinicians

- Translate physiology and research evidence into terms engineers and data scientists can act on

Qualifications

Minimum

- 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

- 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.