KubeCon + CloudNativeCon Europe 2025

In the era of AI-driven innovation, Kubernetes is fundamental for enabling medical scientists to execute machine learning tasks within a containerized environment. However, building a scalable ML platform on Kubernetes presents challenges, especially with advanced on-premise GPU-accelerated hardware optimized for large language model (LLM) training and inference.

This session will explore the obstacles faced by ML engineers and data scientists at Novo Nordisk in creating a robust platform for AI-driven drug discovery. The presentation will discuss enabling access to GPU resources at scale, orchestrating extensive data planes, efficiently running high-performance computing (HPC) jobs, and using GPU sharing strategies and different batch scheduling job software.

Insight about experiences with GPU sharing strategies, batch scheduling job software, overcoming operational challenges, and empowering ML engineers in accelerating drug discovery will be shared.