Machine Learning/AI Engineer

CampTek.ai is hiring a Machine Learning/AI Engineer to build predictive models, generative AI features, and data science capabilities for healthcare revenue cycle management. The role covers end-to-end model development and deployment on Microsoft Azure, working with healthcare data while meeting security, compliance, and responsible AI requirements.

Responsibilities:

• Build models for denial prediction, underpayment detection, propensity to pay, and work prioritization using claims, remittance (835/837), and EHR data
• Run exploratory analysis and root-cause studies that uncover revenue leakage and turn findings into client recommendations
• Define evaluation metrics, run rigorous experiments, and communicate results to technical and business audiences
• Design and build LLM-powered solutions — retrieval-augmented generation, document extraction, and agentic workflows — using Azure OpenAI and Azure AI Foundry
• Process unstructured documents such as payer correspondence, EOBs, and clinical documentation with Azure AI Document Intelligence and LLMs
• Build prompt, evaluation, and guardrail pipelines to measure and improve accuracy, cost, and latency
• Build data pipelines and features for large, sensitive healthcare datasets using Azure Machine Learning, Azure Databricks or Fabric, and Azure SQL
• Deploy, monitor, and maintain models with MLOps best practices: versioning, CI/CD, drift detection, and observability
• Integrate AI capabilities with our applications and UiPath automations alongside our Full-Stack and RPA developers
• Protect PHI and meet HIPAA and security requirements in every model and pipeline
• Design for explainability, human-in-the-loop review, and auditability so clients can trust AI-assisted decisions

Requirements:

• 3+ years of experience building and deploying machine learning models in production
• Hands-on experience with healthcare data — claims, remittance, EHR data, or ICD-10/CPT/HCPCS coding
• Strong Python and SQL skills and experience with ML frameworks (scikit-learn, XGBoost/LightGBM, PyTorch, or similar)
• Experience building applications with large language models, including RAG, prompt engineering, and evaluation
• Experience with Microsoft Azure AI and data services (Azure OpenAI, Azure Machine Learning, or Azure AI Document Intelligence)
• Ability to explain technical trade-offs clearly to non-technical stakeholders; self-directed in a fully remote team
• Experience working with PHI in HIPAA-regulated environments
• Experience with agent frameworks (Semantic Kernel, LangGraph, or similar)
• Azure AI Engineer Associate or Azure Data Scientist Associate certification