Machine Learning Engineer
Core
Design and deploy autonomous, conversational AI agents to triage patient messages and manage clinical workflows within a patient engagement platform.
Role type
Senior Machine Learning Engineer (AI Agents & Conversational NLP)
Builds
Autonomous multi-agent systems, conversational AI interfaces, and tool-calling architectures for clinical workflows.
Domain
Healthcare technology / AI-enabled patient engagement
Deliverable
production ML models
Required skills
AI agents and conversational NLP systems, LangGraph, AutoGen, CrewAI, fine-tuning models, evaluation frameworks (RAGAS, DeepEval), guardrails and alignment techniques, AWS, Databricks, Python
Preferred skills
No-code/low-code agent frameworks, hallucination detection, bias detection, failure mode analysis, CI/CD pipelines for ML deployment
Technologies
LangGraph, AutoGen, CrewAI, NeMo Guardrails, RAGAS, DeepEval, AWS, Databricks
Responsibilities
Design and deploy multi-agent systems for complex clinical workflows; Build and optimize conversational AI interfaces for message triage and sentiment analysis; Implement evaluation frameworks to measure model and agent performance; Implement guardrails to ensure agent safety and HIPAA compliance; Create dashboards to monitor agent reasoning traces and system performance.
Seniority
Senior, hands-on IC
