Job Description

We are looking for a Lead DevOps/MLOps Engineer to join our Data Science Department and work with the ML Engineering team to build out and harden our on-premises, GPU-backed ML platform. In this role, you will help enable multiple ML and LLM use cases to run simultaneously, reliably, and with low latency, while scaling the platform to support a wider user base across the organization.

Responsibilities

Build and harden the on-premises GPU-backed ML platform to support concurrent ML and LLM workloads
Troubleshoot and resolve daily resource bottlenecks and latency issues across competing production and development use cases
Deploy and maintain the NVIDIA GPU Operator and manage GPU resources across Kubernetes and OpenShift clusters
Implement GPU sharing and isolation strategies to optimize memory and fault isolation across workloads
Scale the GPU environment to accommodate growing compute demands as new H200 servers