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Krishnakaanth Reddy Yeduguru
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
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About
AI/ML engineer with healthcare domain depth who led a HIPAA-compliant, production LLM system at McKesson to automate clinical document understanding—extracting entities, summarizing provider notes, and supporting authorization decisions. Hands-on across Spark/Python ETL, Hugging Face + LoRA/QLoRA fine-tuning, RAG, and cloud-native MLOps (Airflow/Kubernetes/Step Functions, MLflow, blue-green on EKS/GKE), with explicit work on PHI handling and hallucination reduction.
Experience
Education
Key Strengths
- Led end-to-end production AI/LLM system for clinical document understanding and claims workflows
- Deep experience building HIPAA-compliant pipelines (PHI scrubbing, encryption, IAM/VPC access controls)
- Practical hallucination mitigation via validation against gold standards and rule-based post-processing
- Strong MLOps/orchestration across Airflow, Kubernetes, Step Functions, and Dagster with monitoring/alerts and MLflow
- Cloud-native deployment experience including Helm and blue/green deployments on AWS EKS and GCP GKE
- Applied RAG and domain-tuned LLMs to generate clinical summaries and suggest CPT/ICD-10 codes in collaboration with clinicians/compliance
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