Chettaniya Verma
Associate Architect @CareEco
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WORK HISTORY
Associate Architect @CareEco
Define enterprise-wide standards for LLM deployment, agentic framework integration, and ML pipeline architecture across healthcare and insurance domains* Lead model governance strategy including evaluation frameworks, output quality benchmarking, and cross-functional alignment on production AI reliability* Mentor engineering teams on ML system design, responsible AI practices, and scalable model-first architecture patterns
EDUCATION
The University of Manchester
Msc Health Data Science, Health Data Science
Savitribai Phule Pune University
Bachelor of Engineering - BE, Computer Engineering
ABOUT CHETTANIYA VERMA
Healthcare AI is only valuable if clinicians can trust it, systems can scale it, and organizations can govern it. That\'s the standard I build to.I\'m an AI/ML Engineer with 5+ years designing and shipping production-grade machine learning and generative AI systems in healthcare. My work spans the full stack from HIPAA-aligned data pipelines to multi-agent LLM workflows that automate clinical decision-making at scale.What I\'ve built in healthcare- A multi-agent ICD & CPT coding system (LangChain + LangGraph) that automates clinical code assignment from CMS/AMA notes with >84% accuracy directly reducing manual coding burden on care teams - End-to-end RAG pipelines grounded in medical literature and coding guidelines, with a custom LlamaIndex evaluation framework measuring retrieval quality, faithfulness, and coherence - Medallion Lakehouse architecture (Azure Databricks + Delta Lake) processing large-scale healthcare claims data HIPAA-compliant, auditable, ML-ready - A RoBERTa-based cardiovascular disease prediction model trained on UK Biobank data, validated with bootstrapping and evaluated on AUROC/AUPRCHow I work: I sit at the intersection of clinical context and engineering depth. I\'ve collaborated directly with clinicians, co-founders, and cross-functional teams to translate messy real-world healthcare requirements into systems that are accurate, interpretable, and production-ready not just impressive in a notebook.* MSc Health Data Science — University of Manchester* BEng Computer Science — Pune UniversityOpen to: AI/ML Engineer · Clinical AI Engineer · ML Engineer (Healthcare) · Health AI Engineer
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