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Managing a machine learning infrastructure is a great challenge, as its scope covers both common infrastructure tasks – such as cluster management, network, security, container management, and observability – and ML-focused tasks – such as GPU compute, data exploration, distributed training, and model serving. Kubernetes and its prosperous open source ecosystem provides great infrastructure tools (e.g., Knative, Cloud Native Buildpacks, Argo, and Envoy), as well as ML-focused projects (e.g., Kubeflow, KServe, Seldon Core, and KubeRay) that enable infrastructure engineers to build a modern machine learning infrastructure. In this panel, you’ll hear from engineers at Bloomberg, Seldon, and Spotify about how they’re using the Kubernetes ecosystem to provide machine learning infrastructure and their current challenges. Panelists represent a variety of use cases, including end-users and infrastructure providers, as well as both on-prem and cloud-based infrastructures.
Manager of Data Science and Compute Infra, Bloomberg
Keith Laban leads the compute and data science infrastructure efforts at Bloomberg. The teams he manages leverage Kubernetes as the building block of a compute engine with a rich feature set. They build and maintain the components required to address many of the computational and... Read More →
Keshi Dai is a Senior ML Engineer on the Spotify Machine Learning platform team. He has been working on building and managing a centralized Kubeflow platform to help Machine Learning engineers at Spotify to adopt Kubernetes. Recently, he is also leading the effort to evaluate managed... Read More →
Yuzhui Liu leads the Data Science Runtime team at Bloomberg. Her team manages an on-prem Kubernetes-based machine learning infrastructure that is used to address Bloomberg’s evolving data science needs. She is actively involved in the Kubernetes open source ecosystem as both a contributor... Read More →
Having previously led a tech team at IBM and now Head of Developer Relations at Seldon, Ed comes from a cloud computing background and is a strong believer in making deployments as easy as possible for developers. With an education in computational modeling and an enthusiasm for machine... Read More →
Thursday October 27, 2022 5:25pm - 6:00pm EDT
251 ABC
