Deepesh Khamat

MLOps / AIOps Research

• Job Details:Designed and implemented scalable, MLOps architecture using Azure Data Factory, Azure Machine Learning Studio, and Azure Kubernetes Service (AKS) to automate the end-to-end machine learning model lifecycle, ensuring seamless deployment and scalability. Conducted a comprehensive study on leading platforms like Amazon Sagemaker, Azure ML Studio, and Google Vertex AI to evaluate and integrate best practices into the platform architecture. Created and managed CI/CD pipelines for machine learning models on Microsoft Azure, ensuring efficient version control, model governance, and automated deployment with Kubernetes and Docker. Developed monitoring frameworks using Azure Monitor, Prometheus, and Grafana to track model performance, optimize workflows, and ensure real-time model reliability. Integrated Ollama LLM model in a Kubernetes cluster, along with Hugging Face models and transformers, to test and enhance AI operations (AIOps) for improved model performance. Collaborated as data engineer, MLOps engineer, and data scientist with cross-functional teams, reducing model deployment time by streamlining processes, and creating technical documentation.

IT Infrastructure Engineer

• Job Details:Monitored file transmission servers 24x7, ensuring seamless operations and swift troubleshooting of issues. Refined existing SOPs and developed new ones to address emerging issues, improving operational efficiency. Scheduled and managed timely jobs for secure file transmissions between financial institutions, ensuring accuracy and compliance with SLAs for financial organizations like BlackRock, JP Morgan, Morgan Stanley and many more. Played a critical role as part of the audit team alongside KPMG, auditing the entire monitoring system. Managed end-to-end file transmission pipelines for efficient and secure data transfer, engaging with a diverse portfolio of 2000+ clients. Gathered business and technical requirements from clients, facilitating the formulation of tailored solutions to meet specific needs. Collaborated closely with onshore and offshore teams to drive project deliverables, demonstrating exceptional communication and coordination skills.