Data Scientist & AI Leader with more than a decade of experience in drivingbusiness transformation through data analytics and AI.Spearheaded engineering initiatives for AI and analytics across JIO Cloudxp,HiveCenter, Cloud360, and Lexicon.Experience in developing end to end Gen AI & Machine Learning SaaSproducts.Worked on designing Scalable solution for big data (In Terabytes).Areas of Expertise:• Generative AI : Llama , Mistral, OpenAI GPT-3, GPT-4, BERT, Langchain,LangGraph, Transformers (Hugging Face).• Data Science and Analytics : Pandas, NumPy, Matplotlib, Seaborn.• Database Design: MySQL, PostgreSQL, NOSQL, Redis, Elastic.• Machine Learning : Regression, Classification, Clustering, Forecasting, NaturalLanguage Processing, Modeling, XGBoost, Light GBM , Spacy, OpenCV, Dlib,Machine Learning System Design.• Deep Learning Frameworks: Tensorflow, Keras, pytorch.• Programming Languages : Python, C, Java, Javascript, PHP.• Big data processing Frameworks : Aache spark, hadoop, Kafka, Dask.• SDLC : Agile scrum, Waterfall.• Version Control Systems and CICD Tools : Git, Github, Azure Devops.• Containerisation and Orchestration : Docker, Kubernetes.Professional Highlights:Patent Holder: System and method for building a knowledge base of dependencies between configuration itemsCreated a robust image deduplication system capable of processing a dataset of500 million human face photos, leveraging Apache Spark and Azure DataFactory pipelines on Azure Synapse to achieve a scaling capacity of 1 billionimages.• Built a comprehensive MLOps platform with MLFlow and Evidently.ai, ensuringthe operational management of 80+ JioCloud models, resulting in a 50%decrease in model monitoring time and increased productivity.• Architected a Generative AI studio that accommodates 20 diverse use cases,deploying Mistral and Llama alongside Azure OpenAI utilizing Langchain andLangraph, vector stores for optimal performance.• Led the migration of on-premise data infrastructure to Azure Data Lake, resultingin a 30% reduction in storage costs and enhanced data accessibility.• Led workshops and design sessions to develop and refine Generative AIsolutions, focusing on LLMs and RAG workflows, while training and enhancingmodels for better content generation and information retrieval.• Planned and refined high-performance machine learning models for dataparallelisation and model parallelisation using TensorFlow and PyTorch for bigdata use cases.