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Saisureshreddy Challa
Mid-level Data Scientist specializing in AI/ML, LLMs, and domain analytics
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About
BlackRock AI/ML engineer who built and owned a production LLM document intelligence system for regulatory and investment analysis end-to-end. They combined RAG, multi-agent validation, strong evaluation/monitoring, and reusable Python services to process 50K+ documents, cut review time 40-50%, and improve decision accuracy by about 25%.
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Key Strengths
- Owned end-to-end production AI systems from experimentation through deployment and monitoring
- Built LLM/RAG document intelligence platform at BlackRock for regulatory and investment documents
- Scaled ingestion and retrieval pipeline across 50K+ documents
- Strong focus on hallucination reduction through retrieval tuning, grounded prompting, validation, and fallback logic
- Production-minded evaluation and monitoring using labeled data, automated checks, and user feedback loops
- Balanced latency, cost, quality, and safety in multi-agent LLM systems
- Improved document review time by 40-50%
- Improved decision accuracy by roughly 25%
- Created reusable Python services with clear APIs, testing, CI/CD, and AWS deployment
- Improved team velocity by reducing integration time from weeks to days
- Used staged rollouts, canary deployments, and feature flags to prevent regressions and protect dependent teams
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