Rishabh Shah

I recently completed my Master’s in Artificial Intelligence at Duke University, where I specialized in MLOps, machine learning, generative AI, and large language models. At Duke, I worked on projects involving scalable pipelines, model optimization, and explainable AI, applying these skills to real-world problems.

Before pursuing my Master’s, I was a Data Scientist at IBM, where I contributed to the development and deployment of IBM’s Content Intelligence platform, an Azure-based document intelligence solution. My responsibilities included designing and deploying the platform on Azure Kubernetes Services using Terraform and Jenkins. I also enhanced its capabilities by integrating Azure Form Recognizer for in-depth invoice analysis and developed custom key-value pair recognition models to improve document processing accuracy. Additionally, I played a key role in optimizing the platform’s performance, which resulted in significant cost and time savings for enterprise clients.

At Nokia Bell Labs, I worked as a Machine Learning Engineer Co-op, focusing on cutting-edge AI solutions. I developed a multi-agent Retrieval-Augmented Generation (RAG) chatbot leveraging Llama 3.1 B8 and BGE-M3 embeddings, fine-tuned QLoRA models to enhance query performance by 25%, and designed scalable pipelines for data processing. This role deepened my expertise in large-scale machine learning and natural language processing systems.

I hold a Bachelor of Technology in Computer Science from NIIT University, where I cultivated a strong foundation in machine learning and artificial intelligence. During my time there, I gained hands-on experience through internships at IBM Consulting and Prescience Decision Solutions, contributing to various machine learning projects ranging from predictive analytics to recommendation engines.

Some projects I have worked one IBM Consulting Global Intelligent Workflows on Azure, IBM Consulting Global AI at Scale on Azure

I am passionate about building robust, production-grade machine learning systems, with a particular focus on MLOps, scalable model deployment, and AI-powered decision-making systems. I thrive in fast-paced environments where I can leverage my skills to develop impactful products that solve real-world challenges at scale. Feel free to connect if you’d like to discuss my work or explore potential collaborations.