Abhishek Tiwari

Assisted clients with AI-LLM projects, conducting comprehensive research, managing large datasets on Azure, and leveraging insights from recent research for model implementation. Built small language models tailored to project requirements, leveraging knowledge of transformer model architecture and utilizing chain-of-thought prompting to enhance model reasoning capabilities. Conducted LLM fine-tuning, parameter optimization, and implemented model building using API tools, integrating transformer architectures such as LoRA ConfigTransformer, while referencing and implementing techniques from recent research papers.

Developed and tested custom variants of machine learning and deep learning algorithms in Python, including Sequential Pattern Mining, Episode Mining, Clustering, and Root Cause Analysis. Implemented models such as Support Vector Machines (SVM), Transformer, Bi-LSTM. Created APIs for these algorithms using FAST API Backend, ensuring accessibility and ease of integration. Established and optimized databases for efficient data management and application performance. Designed and Developed the entire backend infrastructure of the application, overseeing testing procedures to ensure functionality and reliability.