Senior AI/ML Engineer at Capital Cortex

Led creation of an enterprise data lake on Azure consolidating data from AWS and GCP to provide a unified data source, resulting in a 30% improvement in data processing efficiency. Directed design and deployment of ML and NLP models via microservices architectures, supporting batch and real-time prediction systems, improving prediction accuracy by 20%. Spearheaded the use of JupyterLab-based AI notebooks to facilitate iterative model development and streamlined experimentation, accelerating deployment cycles by 25%. Managed end-to-end deployment of ML pipelines using Docker and Kubeflow, creating automated monitoring tools that decreased model downtime by 15%. Utilized IAM and Terraform for efficient management of development, test, and production environments, reducing resource allocation errors by 10%. Led Agile sprints, driving collaboration across cross-functional teams to meet project milestones on time and within budget.

AI/ML Engineer at In Data Labs

Built and maintained ML Ops workflows for large-scale model deployment, reducing downtime by 30%. Implemented NLP solutions for document parsing, increasing processing accuracy by 20%. Designed generative AI workflows to automate content creation, improving productivity by 30%. Developed real-time monitoring system integrated with Twilio, enhancing system responsiveness. Created visual dashboards with Tableau for better stakeholder communication of insights.