Hire Nagaraj K. - RAG Engineer

* Responsibilities: * Designed and developed backend components for enterprise Generative AI applications. * Built an LLM-based Key-Value Information Extraction solution for processing client-uploaded documents. * Developed document processing pipelines using Python, LangChain, and Azure OpenAI. * Integrated GPT-4.1 Vision Language Model (VLM) for extracting structured information from documents. * Implemented embedding generation using OpenAI Embedding Models. * Utilized ChromaDB and FAISS for vector storage and semantic retrieval. * Developed Streamlit-based interfaces for interacting with AI workflows. * Stored extracted structured information in MySQL for downstream reporting and business processing. * Improved document processing efficiency by automating manual extraction workflows. * Reduced document processing time by 70% through AI-driven automation. * Improved data ingestion accuracy and processing speed by replacing manual data entry with automated AI extraction.

* Developed and deployed Machine Learning models using Python, Scikit-learn, TensorFlow, and Keras for classification and regression problems. * Performed Exploratory Data Analysis (EDA), data preprocessing, feature engineering, and data transformation to improve model performance and accuracy. * Implemented supervised Machine Learning algorithms, including Linear Regression, Logistic Regression, Decision Trees, Random Forest, and XGBoost, based on business requirements. * Built Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) models for image classification and predictive analytics. * Evaluated model performance using appropriate metrics and optimized models through hyperparameter tuning and feature selection techniques. * Developed end-to-end Machine Learning pipelines for data preparation, model training, testing, validation, and prediction. * Utilized NumPy, Pandas, Matplotlib, and Scikit-learn for data manipulation, visualization, feature engineering, and model development. * Worked with structured and unstructured datasets to build predictive models and generate actionable business insights. * Performed model validation, debugging, and performance analysis to improve model accuracy, robustness, and reliability. * Collaborated with business stakeholders to understand project requirements, translate business problems into Machine Learning solutions, and document technical workflows. * Maintained source code using Git and Visual Studio Code, following coding standards and version control best practices. * Prepared technical documentation, model evaluation reports, and implementation guides to support deployment and knowledge transfer.