AI Engineer (LLMs for Healthcare)

Keebler Health is building the operating system for value-based care, aiming to empower healthcare organizations with data-driven insights. The AI Engineer will develop and fine-tune large language models for healthcare applications, collaborating with professionals to enhance workflows and ensure compliance with healthcare standards.

Responsibilities:

• Fine-tune and optimize large language models (LLMs) to address specific healthcare applications
• Develop and apply advanced prompt engineering techniques to enhance model outputs for clinical scenarios
• Implement Retrieval-Augmented Generation (RAG) systems to improve knowledge retrieval from large datasets
• Work with knowledge graphs to organize and integrate healthcare-specific data for enhanced decision-making
• Evaluate black-box models using precision, recall, and other performance metrics, ensuring robustness and reliability
• Collaborate with healthcare professionals to understand workflows and identify opportunities for AI-driven enhancements
• Design and build AI models that align with healthcare standards and regulations (e.g., HIPAA compliance)
• Integrate domain-specific knowledge of healthcare data, including FHIR and interoperability standards, into AI solutions
• Develop and maintain scalable, production-ready AI pipelines using MLOps tools
• Deploy and monitor AI models in production environments to ensure performance and compliance
• Optimize infrastructure for efficient training, testing, and deployment of models
• Stay at the forefront of advancements in AI, especially in healthcare applications
• Identify and resolve performance bottlenecks in AI workflows
• Explore emerging trends and technologies in LLMs and healthcare to continually improve solutions
• Partner with cross-functional teams, including data engineers and clinicians, to ensure seamless integration of AI into healthcare workflows
• Communicate technical results and insights effectively to non-technical stakeholders