Lead Applied Scientist, Healthcare AI & Gen AI

Amazon Web Services (AWS); Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Job summary

AWS Healthcare AI seeks an Applied Scientist to lead research and develop confidential AI applications for end customers, clinicians, and staff. You will guide a team of scientists in natural language understanding, foundation models, and reinforcement learning, translating research into scalable, impactful products.

The role requires hands-on technical leadership, defining evaluation methods and ensuring research translates into real-world healthcare solutions with high impact across teams.

Qualifications

• PhD or Master’s degree with 6+ years of applied research experience.
• 3+ years of building ML models for business applications.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.
• 8+ years of building large-scale ML and AI solutions at Internet scale.

Responsibilities

• Lead pioneering research and development of new AI applications.
• Guide a team of scientists in generative AI-powered experiences.
• Define research directions, develop ML techniques and conduct rigorous experiments.
• Translate research into impactful products and set standards for scalable solutions.

Skills

Applied research

ML model development

Programming (Java/C++/Python)

Neural deep learning

Large-scale ML systems

Education

PhD or Master’s degree

Tools

TensorFlow

scikit-learn

Spark MLlib

MxNet

NumPy/SciPy

Job description

AWS Healthcare AI seeks an Applied Scientist to lead research and develop confidential AI applications for end customers, clinicians, and staff. You will guide a team of scientists in natural language understanding, foundation models, and reinforcement learning, translating research into scalable, impactful products.

The role requires hands-on technical leadership, defining evaluation methods and ensuring research translates into real-world healthcare solutions with high impact across teams.