Keebler Health is seeking a talented and motivated mid to senior level AI Engineer with expertise in developing and fine-tuning large language models (LLMs) for healthcare applications.

Company: Keebler Health

Role: AI Engineer (LLMs for Healthcare)

Experience:

Proven experience in LLM fine-tuning and advanced prompt engineering
Hands-on experience with retrieval-augmented generation (RAG) techniques
Expertise in evaluating AI models using performance metrics like precision, and recall

Key Skills:

Python
modern ML frameworks (e.g., Huggingface, pyTorch)
Retrieval-Augmented Generation (RAG) systems
knowledge graphs
MLOps tools
FHIR and interoperability standards

Qualification:

Strong background in Python and modern ML frameworks
Familiarity with healthcare workflows and regulatory requirements (e.g., HIPAA, FHIR standards)

Role Focus: • 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 • 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)

Additional responsibilities:

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
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

Nice to have:

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)

Other:

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

AI Engineer (LLMs for Healthcare)

Skills Required

Description