Continuous training and deployment capabilities have become recurrent discussion topics when talking to data science teams, regardless of industry type or company size. They continually surface as the primary obstacles to deploying and managing ML models as part of business applications. It turns out that Machine Learning Operations (MLOps) emerged as the enabler of continuous training and deployment for ML models.
Staff Solutions Architect
Chris Gully is a Staff Solutions Architect on the Partner Solution Engineering Innovation team in the VMware OCTO. Chris has over 20 years of professional experience ranging from Systems Engineering to Cloud Services Product Management. Currently, he is focused on bringing virtualization to the world of High Performance Computing (HPC) and using VMware software solutions to enable the integration and proliferation of AI/ML workloads, with an emphasis on business and customer outcomes. Previous roles at Dell, Oracle, Sun Microsystems, and several start-ups have prepared him for the speed at which technology and innovation must move to keep customers and businesses relevant. When not devising new ways of applying emerging technology to solve the problems of today and tomorrow, Chris likes “Keepin’ It Weird” with the live music scene in Austin, Texas, and spending time with his family and friends.