Pradeep Dorairaj

Join this session to learn how Snowflake ML enables teams to deploy multimodal models — from Hugging Face or custom builds — directly within Snowflake. By natively supporting image, audio and text, organizations can run large-scale inference on unstructured data without managing complex infrastructure.

In this session, learn more about Snowflake’s end-to-end ML platform and how it supports creating production-scale deployments and operationalization of your models. We will dive into MLOps essentials and Snowflake’s capabilities for model management and model serving. You can easily bring models trained externally, or train them at scale using Snowflake ML, and then securely and scalably deploy them for inference with our flexible serving environments. At the end, we’ll bring this to life with a real-life scenario of managing production models, running continuous evaluations to train and deploy champion-challenger models.