About the Role:
Own the development and fine-tuning of multi-modal ML models powering diagnosis, image-to-text processing, symptom analysis, and intelligent routing for Care Access PBC global care access engine.
Responsibilities:
- Build and deploy LLM- and vision-enhanced models for patient intake, symptom description, and medical form analysis.
- Preprocess structured, semi-structured, and unstructured healthcare data.
- Tune open-source models (LLaMA, Phi-3, MedPaLM, etc.) for performance and safety.
- Contribute to real-time inference pipelines and monitoring dashboards.
Requirements:
- 5+ years ML engineering experience; strong in NLP and CV.
- Experience with model compression, retrieval-augmented generation (RAG), and healthcare-specific embeddings.
- Strong hands-on skills with vector databases, streaming pipelines, and deployment tools.
- Publications or projects in healthcare AI a big plus.
