This panel will feature several machine learning and MLOps engineers sharing their experiences using Argo Workflows. We will talk about the goals each company set out to achieve when building their machine learning platforms, the role Argo Workflows plays, and what to keep in mind when designing user interfaces for the team.

The panelists will highlight the use cases that Bloomberg, Dyno Therapeutics, and Centrica solve with Argo Workflows in the financial, bioinformatics, and energy sectors. The primary focus will be on the balancing act between achieving high scale and appropriately abstracting complexity so that each organization's ML teams can move quickly.