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Sriram Degala
Senior AI/ML Engineer specializing in healthcare and finance AI
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About
Built production-grade medical AI systems at MD Anderson, including an end-to-end RAG chatbot used by clinical researchers for real-time drug interaction and trial literature queries. Stands out for combining healthcare domain knowledge with strong MLOps, evaluation, and safety practices, and for delivering measurable gains in latency, retrieval precision, and team adoption.
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Key Strengths
- Built a production medical RAG chatbot end-to-end
- Strong healthcare AI domain expertise
- Improved response time by 40% through chunking optimization
- Delivered 60% faster literature lookup for clinical teams
- Balanced latency, cost, quality, and safety in production LLM systems
- Improved retrieval precision by 35% with entity-aware chunking
- Implemented robust LLM evaluation and safety guardrails
- Designed reusable Python services adopted by multiple research teams
- Enabled self-service deployment with containerized CI/CD
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