Keebler Company Jobs (NOW HIRING)

Job Summary:
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 optimize 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.
Qualifications:
Required:
• 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.
Preferred:
• 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).
Company:
Keebler Health develops an AI-powered healthcare analytics platform focused on risk adjustment and clinical decision support. Founded in 2023, the company is headquartered in Durham, USA, with a team of 11-50 employees. The company is currently Early Stage.