Senior ML Engineer - GenAI, RAG & NLP for Healthcare

Judi Health, LLC; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Judi Health is seeking a Senior Machine Learning Engineer to advance AI capabilities in pharmacy benefits, applying NLP, GenAI, and RAG techniques. You will design scalable ML systems, build backend services in Python, and implement multi-agent orchestration while ensuring secure handling of healthcare data.

The role emphasizes collaboration across product and engineering in a fast-paced startup, with a focus on deploying high-performance AI models in production and measuring impact with robust

Qualifications

• BS/MS in CS or related quantitative field.
• 4+ years of industry experience in ML solutions and deployment.
• Strong Python and PyTorch skills; experience with NLP/GenAI.
• Familiarity with cloud platforms (AWS/Azure) and containerized deployments.
• Experience designing evaluation frameworks for non-deterministic AI systems.

Responsibilities

• Design, develop, and productionize ML solutions for NLP, QnA, GenAI, and agents.
• Build backend services in Python for AI-driven applications.
• Create APIs for AI model integration and orchestration patterns.
• Scale RAG architectures; manage vector search and embedding pipelines.
• Collaborate with product and engineering across rapid, startup timelines.
• Lead ML lifecycle from problem framing to deployment and monitoring.
• Implement telemetry, A/B testing, and automated validation.
• Ensure HIPAA-compliant security and data governance.

Skills

Machine Learning

Python

NLP

GenAI

LLMs

RAG

Multimodal AI

Code review

Collaborative teamwork

Education

Bachelor’s or Master’s in CS/ML

Tools

PyTorch

AWS

Azure

Containerization

GenAI services

Job description

Judi Health is seeking a Senior Machine Learning Engineer to advance AI capabilities in pharmacy benefits, applying NLP, GenAI, and RAG techniques. You will design scalable ML systems, build backend services in Python, and implement multi-agent orchestration while ensuring secure handling of healthcare data.

The role emphasizes collaboration across product and engineering in a fast-paced startup, with a focus on deploying high-performance AI models in production and measuring impact with robust