Hire Ritesh T. - Prompt Engineer

Prompt Engineer & Data Annotation Specialist Contributing to the development and evaluation of AI/LLM systems through large-scale data annotation, prompt engineering, and quality assurance workflows. Designed and refined prompts to improve model performance, conducted complex data labeling tasks, and ensured dataset accuracy through rigorous validation processes. Collaborated with cross-functional teams to support model training, benchmarking, and continuous improvement of generative AI applications

Prompt Engineer | NVIDIA Data Factory Improving AI model performance through prompt engineering, data annotation, response evaluation, quality assurance, and structured feedback for large-scale language model training and alignment.

Built an end-to-end supervised learning pipeline to classify Iris flowers into three species (Setosa, Versicolor, Virginica) using key features like petal and sepal dimensions; utilized the UCI Iris dataset for model development and experimentation. Implemented and compared multiple algorithms including Logistic Regression, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). Performed hyperparameter tuning and model evaluation using accuracy, confusion matrix, and cross-validation techniques. Achieved over 95 percent test accuracy visualized data distributions and decision boundaries using Matplotlib and Seaborn.