Amazon
Applied Science Manager, Healthcare AI
$184K–$249K
Seattle, WA · Manager · Full-time · Posted Jun 19, 2026
- Experience
- 2+ years managing scientists or machine learning engineers; PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience.
- Education
- PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience.
About the job
Leads applied science and data teams building AI-powered healthcare products for clinical and administrative workflows, from research and technical strategy through production delivery.
What you'll do
- Build, lead, and mentor Applied Scientists and ML Engineers while setting technical and research direction.
- Drive innovation in medical administration reasoning systems, AI agent design, and medical coding.
- Collaborate across teams to productionize research and manage project portfolios and resources.
What they ask for
- 2+ years of scientists or machine learning engineers management experience.
- Knowledge of ML, NLP, Information Retrieval and Analytics; experience in applied research.
- PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience.
- Programming experience in Java, C++, Python or a related language; experience in at least one listed area such as algorithms and data structures, parsing, numerical optimization, data mining, or distributed computing.
Nice to have
- Experience building machine learning models or developing algorithms for business application.
- Experience delivering complex software systems involving deep learning, machine learning, computer vision, speech recognition, or natural language processing to customers.
Pay
183,800.00 - 248,700.00 USD annually (base salary)
Tools
ML, NLP, Information Retrieval, Java, C++, Python, computer vision, deep learning
AI focus
Develops generative and agentic AI healthcare products, including medical administration reasoning systems, AI agent design, medical coding, clinical documentation, and health data analytics.
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