Design and build LLM-powered applications for patient communication and care navigation
Develop predictive models for patient engagement, risk stratification, and care optimization
Build robust evaluation frameworks and metrics to measure model quality, safety, and clinical appropriateness
Architect ML systems that handle diverse healthcare data sources while maintaining privacy and compliance
Optimize model performance for latency, cost, and quality across production workloads
Collaborate with product and clinical teams to translate healthcare problems into ML solutions
Stay current on ML research and bring relevant innovations into production applications
Partner with backend engineers to integrate ML systems into the broader platform architecture

Requirements

5+ years of experience in machine learning engineering with at least 2 years working with LLMs or NLP systems
Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face)
Hands-on experience building and deploying LLM-based applications in production
Deep understanding of modern ML techniques: fine-tuning, prompt engineering, RAG, embedding models
Experience designing evaluation frameworks and metrics for ML system quality
Strong software engineering fundamentals with ability to write production-quality code
Excellent problem-solving skills and ability to translate ambiguous requirements into technical solutions

Benefits

Competitive salary and equity package
Flexible work environment and remote options
Comprehensive health, dental, and retirement benefits
The chance to make a significant impact in a mission-driven startup focused on transforming patient care
Location: NYC, SF, or Remote
Expected Start Date: Feb 2026

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learning engineeringLLMNLPPythonPyTorchTensorFlowHugging Facefine-tuningprompt engineeringembedding models

Soft Skills

problem-solvingcollaborationcommunication