I’m a full-stack AI/ML engineer with a healthcare focus, and I’m currently open to new opportunities — especially in AI/ML and full-stack roles working with sensitive-data and healthcare domains.
What I keep coming back to: being the sole/founding engineer behind LLM- and computer-vision-powered healthcare platforms, end to end — frontend → AI services → data/EHR integration → cloud.
Most recently, I was the full-stack engineer on a production LLM platform that matches patients to clinical trials, working solo across a Next.js 14 / React / TypeScript frontend and two Python backends (a gRPC matching API and a FastAPI EHR-ingestion service). That work spanned LLM-based eligibility matching and evaluation (litellm/OpenAI), FHIR R4 / EHR data integration, and GCP (Cloud Run, Firestore, Pub/Sub).
Before that, I founded the engineering at HealthyMe AI, a NYC-based healthcare-AI startup building computer-vision models to help practitioners diagnose dermatological disease. As the first technical hire and chief architect, I built the platform from the ground up — the dataset platform of pathologically proven images, all core AI models, and the pipeline connecting our diagnostic technology directly to clinical EHR systems — and grew the technical foundation as the team scaled.
Across my career as a Machine Learning Engineer and Data Scientist, I’ve applied ML, MLOps, and data engineering to projects in scientific research, manufacturing, and healthcare. I hold a master’s degree in computational data science from Drexel University.
📄 Resume: cm_resume.pdf
Schedule some time to chat! https://calendly.com/clnjmurph/30min
- Overview of HealthyMe (Founding Work and Achievements)
- End-to-End system for dermatological diagnostic support within EMR (Infrastructure as code build)
- AI Inference Microservice (Overview of an inference microservice, part of ai-ddx-assist)
- Dermatology Annotation App (Multi-User Dermatology Image Annotation Platform)
- Dermatological Disease Classification (Overview of challenges and solutions)