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Prasanna Chelliboyina
Mid-level Machine Learning Engineer specializing in forecasting, NLP, and GenAI
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GenAI/ML engineer with production experience building multilingual LLM systems (English/Spanish) and RAG-based clinical documentation summarization at Walgreens, combining prompt engineering, structured output validation, and rigorous evaluation (ROUGE + pharmacist review). Also orchestrated end-to-end ML pipelines for demand forecasting using Apache Airflow, PySpark, and MLflow with scheduled retraining and production monitoring.
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Key Strengths
- Built and deployed multilingual LLM comment-routing system (English/Spanish) with ~15% macro F1 improvement vs rule-based baseline
- Improved LLM reliability via few-shot prompting and structured JSON output validation
- Hands-on ML production orchestration with Airflow (automated ingestion, PySpark feature engineering, training, deployment, scheduled retraining)
- Designed and evaluated RAG workflow with both automated metrics (ROUGE) and expert human review (pharmacists)
- Production monitoring focus: accuracy, latency, and retrieval quality via logging/dashboards
- Cross-functional collaboration with non-technical stakeholders (pharmacists, operations) to translate workflows into model requirements
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