AI Engineer (LLMs for Healthcare)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

We are seeking a mid to senior level AI Engineer focused on developing and fine-tuning large language models for healthcare. You’ll optimize LLMs, design prompt engineering strategies, implement RAG systems, integrate healthcare data standards like FHIR, and collaborate with clinicians to deploy production-ready AI pipelines in value-based care workflows.

Location: Durham

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Fine-tune and optimize large language models (LLMs) for healthcare applications and clinical scenarios.
•Develop and apply advanced prompt engineering techniques to improve model outputs.
•Implement Retrieval-Augmented Generation (RAG) systems to enhance knowledge retrieval from large datasets.
•Work with knowledge graphs to organize and integrate healthcare-specific data for better decision-making.
•Evaluate models using precision, recall, and other metrics to ensure robustness and reliability.

Key Requirements

•Proven experience in fine-tuning large language models (LLMs) 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 metrics such as precision and recall.

Experience:Healthcare

Skills:CollaborationProblem-solvingCommunication

Languages:English

Tech Stack:PythonHuggingfacePyTorchRAGFHIRHL7AWSGCPAzureDockerKubernetesMLflowLangfuseLightningPyTorch Lightning

Company Brief

Keebler Health

Keebler Health develops digital health solutions focused on improving patient outcomes through technology-driven care management, remote monitoring, and clinician support tools tailored for chronic disease management and care coordination.

Industry: HealthTech

Website

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Keebler Health

5 months ago

AI Engineer (LLMs for Healthcare)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: Durham

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Fine-tune and optimize large language models (LLMs) for healthcare applications and clinical scenarios.
•Develop and apply advanced prompt engineering techniques to improve model outputs.
•Implement Retrieval-Augmented Generation (RAG) systems to enhance knowledge retrieval from large datasets.
•Work with knowledge graphs to organize and integrate healthcare-specific data for better decision-making.
•Evaluate models using precision, recall, and other metrics to ensure robustness and reliability.

Key Requirements

•Proven experience in fine-tuning large language models (LLMs) 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 metrics such as precision and recall.

Experience:Healthcare

Skills:CollaborationProblem-solvingCommunication

Languages:English

Tech Stack:PythonHuggingfacePyTorchRAGFHIRHL7AWSGCPAzureDockerKubernetesMLflowLangfuseLightningPyTorch Lightning

Company Brief

Keebler Health

Industry: HealthTech

Website