As a Senior Machine Learning Engineer – Healthcare AI, you will design, build, and deploy machine learning models using both classical techniques and cutting-edge foundation models (LLMs, vision, etc.). You’ll be responsible for integrating models like those from OpenAI, and customizing them for healthcare-specific applications, including EHR analysis, medical coding, clinical documentation improvement (CDI) and NLP, patient interaction tools, and more.

This role sits at the intersection of engineering, research, and healthcare domain knowledge — ideal for someone ready to lead technical innovation in a high-impact space.

Responsibilities

• Design, train, fine-tune, and deploy ML models for structured and unstructured healthcare data (EHRs, clinical notes, images, etc.).
• Integrate and customize APIs from OpenAI, Anthropic, Hugging Face, and other foundational model providers.
• Evaluate and fine-tune large language models (LLMs) for clinical NLP tasks (summarization, question answering, etc.).
• Collaborate cross-functionally with product managers, data engineers, and clinicians to build AI-powered solutions.
• Implement scalable and compliant MLOps pipelines for model deployment and monitoring.
• Monitor and address model drift, bias, and performance in real-world use.
• Stay up to date with the latest developments in generative AI, foundation models, and healthcare ML.