Note: The job is a remote job and is open to candidates in USA. Keebler Health is building the operating system for value-based care, aiming to empower healthcare organizations with data-driven insights. The role involves developing and fine-tuning large language models for healthcare applications, collaborating with healthcare professionals, and optimizing AI workflows.
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
Skills
• Proven experience in LLM fine-tuning and advanced prompt engineering
• Strong background in Python and modern ML frameworks (e.g., Huggingface, pyTorch)
• Familiarity with healthcare workflows and regulatory requirements (e.g., HIPAA, FHIR standards)
• Hands-on experience with retrieval-augmented generation (RAG) techniques
• Expertise in evaluating AI models using performance metrics like precision, and recall
• Experience with MLOps frameworks such as MLflow, Langfuse, or similar tools
• Understanding of healthcare data standards, including HL7 and HEDIS metrics
• Strong problem-solving skills in integrating AI with complex healthcare datasets
• Familiarity with cloud platforms (e.g., AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
Benefits
• Competitive salary and benefits package.
• Opportunity to work in a fast-paced, innovative environment.
• Professional growth and development opportunities.
• Collaborative and supportive team culture.
• Chance to make a meaningful impact on the healthcare industry.
Company Overview
• Keebler Health is a developer of an AI-based risk adjustment tool for healthcare providers. It was founded in 2023, and is headquartered in Durham, North Carolina, USA, with a workforce of 11-50 employees. Its website is https://keebler.health/.
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