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OBUL REDDY LEKKALA
Mid-level Data Scientist specializing in predictive modeling, NLP/LLMs, and RAG search systems
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About
Built production LLM/RAG platforms for financial services to enable natural-language Q&A over large policy/compliance document sets stored in Snowflake and SharePoint. Strong in MLOps and orchestration (Airflow, ADF, Step Functions, MLflow) and in solving real production issues like stale embeddings and model performance, including an incremental Snowflake Streams sync that cut processing time from hours to minutes.
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Key Strengths
- Built and deployed production RAG-based document intelligence for financial services
- Resolved Snowflake–Databricks data consistency and stale-embedding issues via incremental sync using Snowflake Streams (reduced processing from hours to minutes)
- Performance optimization of large embedding models on Databricks using mixed precision inference
- End-to-end ML/LLM pipeline orchestration across Airflow/ADF/Step Functions/Databricks Jobs with SLAs, retries, and lineage
- Structured reliability approach for agentic/RAG workflows (modular design; unit/scenario/adversarial testing; retrieval/grounding validation before LLM layer)
- Cross-functional delivery with product, compliance, data engineering, DevOps, QA, and domain experts; integrated CI/CD and cloud deployment patterns (AKS/SageMaker)
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