Josh D.
About Josh D.
Josh D. is a Solutions Architect and MLOps Integrator currently working at Redhorse Corporation, where he specializes in developing cloud-based MLOps pipelines for the Department of Defense. He has extensive experience in systems engineering and architecture, having held various roles at companies such as UberEther, Inc. and Cygnacom Solutions.
Current Role at Redhorse Corporation
Josh D. serves as a Solutions Architect and MLOps Integrator at Redhorse Corporation. He has held this position since 2021, contributing to the Digital Solution Division. His work focuses on developing containerized, cloud-based MLOps pipelines tailored for the Department of Defense's Joint Artificial Intelligence Center. He is involved in solutions that encompass training data, model version control, and storage persistence.
Previous Experience at UberEther, Inc.
Prior to his current role, Josh D. worked at UberEther, Inc. as a Director from 2020 to 2021 for 11 months. He also held the position of Systems Engineer, Architect at the same company from 2013 to 2020 for a total of seven years. His experience at UberEther involved overseeing various technical projects and contributing to system architecture.
Experience at Cygnacom Solutions
Josh D. has extensive experience at Cygnacom Solutions, where he held multiple roles. He served as a Senior Solutions Architect for six months in 2012 to 2013. Additionally, he worked as a Systems Integrator from 2007 to 2010 for three years and as a Senior Security Engineer for one year from 2011 to 2012. He also worked as an Operations Manager for seven months in 2010 to 2011.
Educational Background
Josh D. earned a Master of Science (M.S.) degree from George Mason University, studying from 2005 to 2007. He also holds a Bachelor of Business Administration (B.B.A.) from James Madison University, where he studied from 2000 to 2004. His educational background supports his expertise in solutions architecture and MLOps integration.
Professional Skills and Expertise
Josh D. specializes in developing MLOps pipelines that are containerized and cloud-based. His expertise is particularly focused on the needs of the Department of Defense's Joint Artificial Intelligence Center. He works on critical aspects of MLOps, including training data management, model version control, and ensuring storage persistence.