(2nd) AI/Machine Learning Engineer

Position Overview

Citizen Health, founded on the belief that the right advocate is crucial for better care, is building a personalized AI advocate powered by comprehensive healthcare data. We are seeking our 2nd AI/Machine Learning Engineer to lead the development and deployment of cutting-edge AI solutions for rare and complex conditions. In this role, you will transform complex health data into actionable insights for patients, healthcare providers, and researchers.

Key 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 to 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 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
• Lead research initiatives to explore and implement state-of-the-art AI/ML techniques
• Collaborate with clinical experts to validate model outputs and ensure medical accuracy
• Stay current with the latest developments in AI/ML, particularly in healthcare applications

Required Qualifications

• 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
• Strong software engineering skills and coding best practices

Preferred Qualifications

• Hands-on experience integrating and optimizing Large Language Models (LLMs) in production environments
• Proficiency with LLM tools and techniques such as LangChain, LlamaIndex, and Prompt Engineering
• Experience implementing Retrieval-Augmented Generation (RAG) systems
• Familiarity with vector databases and efficient similarity search techniques for AI applications
• Experience with message queuing systems and data streaming platforms
• Familiarity with data processing and analytics technologies
• Proven track record of high-quality coding and architectural design
• Passion for creating robust, scalable, AI-driven systems that make a real-world impact in healthcare

Benefits & Perks

• Competitive salary + equity package
• Comprehensive health, dental, and vision insurance
• Unlimited paid time off, including a generous parental leave
• Flexible hybrid work environment
• Compensation Range: $180K - $230K