Jan 2024 – Aug 2024 · 7 mos · London Area, United Kingdom

Sep 2022 – Jan 2024 · 1 yr 4 mos · Greater London, England, United Kingdom

• Design and Develop MLOps framework to automate the end-to-end machine learning lifecycle, from data ingestion, model training, model management to model deployment.
• Establish robust monitoring and logging mechanisms to detect anomalies and performance degradation in deployed computer vision models.
• Implement version control for computer vision dataset using DVC (Data Version Control) to track changes, manage experiments, and maintain model lineage.
• Designs and manages cloud infrastructure for ML workloads, ensuring scalability, security, and cost optimization to choose the right cloud services and architectures for ML applications.

Nov 2019 – Aug 2021 · 1 yr 9 mos

• Collaborating with data scientists, engineers, and other stakeholders to ensure seamless integration of machine learning models into production systems.
• Developing and maintaining MLOps framework for the logistics management application.
• Deploying, automating, maintaining, and managing cloud-based production systems, to ensure the availability, performance, scalability, and security of production systems.
• Deployment automation with the Kubernetes platform in the public cloud and datacenter clusters.

May 2016 – Nov 2019 · 3 yrs 6 mos · Bengaluru Area, India

• Planning & Migrating legacy systems to the cloud, getting the application cloud native.
• Experienced in Automating, Configuring, and deploying instances on cloud environments and
• Datacenters.
• Automating and maintaining our CI/CD pipeline, source code repositories, and build servers.
• Maintaining application infrastructure, including scalable compute clusters, web servers, and
• databases.
• Continuous monitoring of applications to ensure all are healthy and to set rules/alerts for
• routine and exceptional application conditions