A Staff Research Engineer focused on developing AI and machine learning solutions to create personalized digital healthcare treatments, including building AI care systems and engaging in advanced AI stack engineering to improve clinical care accessibility and quality.
Key Responsibilities
Develop AI and ML solutions for personalized clinical care
Build end-to-end AI treatment management systems across care pathways
Create and optimize AI components such as prompt engineering, RAG implementations, and model fine-tuning
Design and implement agentic workflows for patient engagement and clinical guidance
Leverage generative AI and classical machine learning based on problem requirements
Requirements
Experience developing AI and ML solutions that power personalized clinical care at scale, including end-to-end AI treatment management systems handling complete care pathways from initial assessment through intervention selection and progress monitoring across various therapeutic domains.
Proficiency in prompt engineering, RAG (Retrieval-Augmented Generation) implementations, model fine-tuning, and agentic workflows within AI projects.
Ability to leverage both generative AI and classical machine learning techniques depending on the problem requirements.
Strong understanding of the full AI stack involved in digital healthcare solutions.
Experience working on projects that contribute to delivering digital care with improved clinical quality and accessibility.