Citizen Health is seeking to solve the problem of improving disease understanding, treatment recommendations, and patient outcomes in rare and complex conditions by developing AI-driven solutions that transform complex health data into actionable insights for patients, healthcare providers, and researchers.
Requirements
- 5+ years of experience in machine learning engineering, with a focus on production ML systems
- Strong proficiency in Python and AI/LLM frameworks (LangChain, LangGraph, AutoGen, CrewAI)
- Experience designing and implementing production-grade ML pipelines
- Proven track record of deploying ML/LLM solutions in production environments
- Strong understanding of ML fundamentals, including deep learning, NLP, and statistical modeling
- Experience with ML ops tools and best practices
- Proficiency in working with large-scale datasets and distributed computing
Responsibilities
- Design and implement end-to-end machine learning solutions, from data preprocessing to model deployment and monitoring
- Develop and optimize agentic Large Language Models (LLMs) solutions for healthcare applications using techniques like fine-tuning and Retrieval-Augmented Generation (RAG)
- Create robust data pipelines for validation, and deployment
- Implement ML systems that can effectively process and analyze diverse healthcare data types, including structured clinical data, medical imaging, and unstructured text
- Collaborate with backend engineers to integrate ML models into our production infrastructure
- Ensure ML systems meet strict healthcare compliance requirements while maintaining high performance
- Design and implement monitoring systems for model performance, data drift, and system health
Other
- Degree in Computer Science or equivalent degree
- Competitive salary + equity package
- Comprehensive health, dental, and vision insurance
- Unlimited paid time off, including a generous parental leave
- Flexible hybrid work environment
