Healthcare AI Applied Science Lead

Amazon Inc.; Seattle (WA); On-site; USD 184,000 - 249,000; Full time

Job summary

Amazon.com Services LLC in Seattle, WA seeks an Applied Science Manager to lead science and data teams building AI-powered healthcare solutions on cloud platforms. You will oversee applied scientists and ML engineers, drive research strategy, and translate research into production with cross-functional partners.

The role emphasizes leadership, strategic thinking, and hands-on technical depth in ML/AI, with the chance to shape healthcare workflows and clinical/documentation systems at scale.

Qualifications

• 2+ years of scientists or machine learning engineers management experience.
• Knowledge of ML, NLP, Information Retrieval and Analytics.
• PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business applications.
• Experience in applied research.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing.

Responsibilities

• Build and lead a world-class team of Applied Scientists and ML Engineers.
• Set technical direction and research strategy aligned with business goals.
• Drive innovation in medical administration reasoning systems, AI agent design, and medical coding.
• Collaborate with cross-functional teams to translate research into production.
• Manage project portfolios and resource allocation.

Skills

People management

ML & NLP

Programming: Java, C++, Python

Applied research

Cloud computing

Healthcare AI domain

Education

PhD or MS + 4+ years ML experience

Job description

Amazon.com Services LLC in Seattle, WA seeks an Applied Science Manager to lead science and data teams building AI-powered healthcare solutions on cloud platforms. You will oversee applied scientists and ML engineers, drive research strategy, and translate research into production with cross-functional partners.

The role emphasizes leadership, strategic thinking, and hands-on technical depth in ML/AI, with the chance to shape healthcare workflows and clinical/documentation systems at scale.