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Tadigotla Kumar Reddy
Mid-level AI/ML Engineer specializing in healthcare imaging and GenAI/LLM systems
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Built and deployed a production LLM/RAG clinical document understanding and summarization system for healthcare, focused on reducing manual review time while meeting strict accuracy, latency, and compliance needs. Demonstrates strong MLOps/orchestration depth (Airflow, Kubernetes, Azure ML Pipelines) and a rigorous approach to hallucination mitigation through layered, source-grounded safeguards and stakeholder-driven requirements with physicians/compliance teams.
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Key Strengths
- Built and deployed a production RAG-based clinical document summarization platform
- Designs layered safeguards to reduce hallucinations via controlled context and source grounding
- Strong production orchestration experience (Airflow, Kubernetes, Azure ML Pipelines)
- End-to-end ML pipeline ownership (ingestion → features → training → evaluation → scheduling) with SLAs/alerting and backfills
- Methodical evaluation approach with measurable metrics (accuracy/relevance, latency, cost, failure rates) and component-level testing
- Pragmatic model selection using benchmarking on real data and constraints (latency/cost/explainability/risk)
- Effective collaboration with physicians and compliance stakeholders to translate workflows into system requirements
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