Senior AI Compute Cluster Operations Engineer

Cerebras; Toronto; On-site; CAD 120,000 - 190,000; Full time

Job summary

Cerebras Systems seeks an AI Cluster Operations Engineer to manage the world's largest AI compute clusters, including the Wafer-Scale Engine. You will ensure health, performance, and availability of infrastructure, maximize capacity, and support AI initiatives.

The role requires Linux expertise, Docker/Kubernetes, and experience with monitoring, automation, and distributed systems. You will work with a fast-paced, on-call team to deliver reliable, scalable platforms for cutting-edge AI workloads.

Qualifications

• 6-8 years of experience managing and operating complex compute infrastructure, preferably with ML/HPC context.
• Proficient in Python and Go, with experience building operational platforms and reliability tooling.
• Deep knowledge of Linux-based compute systems and CLI tools.
• Extensive Docker experience and orchestration via Kubernetes.
• Experience with monitoring and alerting systems and troubleshooting complex issues.

Responsibilities

• Deploy, configure, and debug container-based services using Docker.
• Build and own software that powers cluster operations, including dashboards and reliability tooling.
• Collaborate with cross-functional teams to translate requirements into scalable OM platforms.
• Develop APIs, automation services, and integrations for visibility and fleet management.
• Manage and operate multiple advanced AI compute clusters.
• Monitor cluster health and proactively resolve issues to maximize compute capacity.
• Provide 24/7 monitoring and hands-on troubleshooting as needed.
• Handle escalations and collaborate to resolve complex challenges.
• Stay up-to-date with advancements in AI compute infrastructure.

Skills

6-8 years experience

Python

Go

Distributed systems

Linux

Docker

Kubernetes

Troubleshooting

Monitoring/alerts

On-call rotation

Communication

Tools

Docker

Kubernetes

Job description

Cerebras Systems seeks an AI Cluster Operations Engineer to manage the world's largest AI compute clusters, including the Wafer-Scale Engine. You will ensure health, performance, and availability of infrastructure, maximize capacity, and support AI initiatives.

The role requires Linux expertise, Docker/Kubernetes, and experience with monitoring, automation, and distributed systems. You will work with a fast-paced, on-call team to deliver reliable, scalable platforms for cutting-edge AI workloads.