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Jhansi Priya
Mid-level AI/ML Engineer specializing in GenAI, RAG pipelines, and agentic workflows
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About
Applied AI/ML engineer with hands-on production experience building a RAG-based AI assistant for pharmaceutical maintenance troubleshooting using LangChain + FAISS/Pinecone, including a custom normalization layer to handle inconsistent terminology and duplicate document revisions. Also built Airflow-orchestrated pipelines for document ingestion/embeddings and predictive maintenance workflows (SCADA ETL, drift-based retraining), and partnered closely with production supervisors/quality engineers via Power BI dashboards and real-time alerts.
Experience
Education
Key Strengths
- Built and deployed a production RAG assistant for pharmaceutical maintenance troubleshooting
- Strong unstructured document processing (cleaning, chunking, indexing) with terminology/version normalization to improve retrieval quality
- Designed reliable orchestration with Apache Airflow (modular DAGs, sensors, retries) for ingestion, embeddings, and validation
- Scaled embedding workflows by batching/chunking and parallelizing to control memory usage
- Operational ML pipeline experience: scheduled SCADA ETL and weekly retraining driven by drift metrics
- Reliability-focused evaluation approach (synthetic + production tests, confidence thresholds, weekly review using logged feedback)
- Effective collaboration with non-technical stakeholders; translated analytics into actionable Power BI dashboards and alerts
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