Nitesh Yadav

I leverage my expertise in Natural Language Processing (NLP) and Generative AI (GenAI) to actively participate in the development of AI-driven solutions. A key aspect of my role involves seamlessly integrating NLP technologies with Azure's robust capabilities. Throughout my tenure, I make pivotal contributions to various projects, including Langchain, LLamaIndex, Azure OpenAI, Azure Cognitive Services, and Azure Cognitive Search. My focus encompasses prompt engineering, refining search algorithms, and efficiently executing projects by harnessing Azure Form Recognizer and Azure DevOps. I have created a range of products, including website bot driven by language models (LLMs), Teams bot powered by LLMs, document question-and-answer bots, and proposal generator. Worked on Managing vector data using VectorDB and implementing advanced natural language processing with GPT models.

As a key member of the Cashe team, I executed end-to-end Machine Learning processes, covering crucial stages such as Data Preprocessing, Feature Engineering, and Modeling. These efforts substantially augmented the company's comprehension of customer behavior while enhancing existing solutions. I conducted thorough Data Analysis on customer datasets, extracting valuable insights to drive informed decision-making processes. Through adept application of preprocessing and feature engineering techniques, I established a robust Database of customer information, ensuring comprehensive coverage and accuracy in our data assets.

During my tenure at HPE, I led the implementation of advanced Swarm Learning and Deep Learning methodologies, resulting in the successful development of a model achieving an impressive 91% accuracy rate. I proficiently conducted hyperparameter tuning to further refine model performance, employing a range of activation functions and optimizers to achieve optimal results. Demonstrating expertise in Docker, I efficiently deployed and managed machine learning applications, ensuring streamlined deployment processes and effective management of resources. My contributions resulted in my team securing the 1st prize and a reward of Rs 1 lakh.