Senior Machine Learning Engineer – Healthcare AI
Job Description
About Us
We are a fast-growing healthcare technology company dedicated to transforming patient outcomes through innovative digital solutions. As we continue to incorporate advanced AI capabilities into our established Revenue Cycle Managment (RCM) focused solutions, to develop intelligent, scalable, and responsible solutions that directly impact patient experience, process and operational efficiencies, financial decision-making, medical coding, Clinical Documentation Improvement (CDI) , and health insurance claims.
About the Role
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.). Youll 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.
- 5+ years of experience in applied machine learning or AI engineering.
- Proficiency in Python and ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
- Hands-on experience using OpenAI APIs and working with foundation models (e.g., GPT, Claude, Mistral, LLaMA).
- Experience fine-tuning or prompt-engineering LLMs for specific tasks.
- Strong engineering background, including building and deploying models in production.
- Experience working with healthcare datasets (EHR, Insurance Claims, CDI, Autonomous Coding, FHIR) is strongly preferred.
- Understanding of compliance frameworks (HIPAA, GDPR, FDA SaMD) in AI deployments.
- Solid grasp of ML interpretability, evaluation metrics, and ethical AI principles.
- Strong communication skills and ability to work in cross-functional teams.
- Experience with retrieval-augmented generation (RAG) or knowledge-grounded LLMs.
- Familiarity with multimodal models (e.g., combining images + text).
- Hands-on experience with MLOps platforms like MLflow, TFX, Airflow, or SageMaker.
- Prior work in clinical NLP, patient triage automation, or diagnostic support tools.