Site Reliability Engineer, AI​/ML Infrastructure

Site Reliability Engineer, AI/ML Infrastructure

Base pay range: CA$/yr - CA$/yr

About The Role We're looking for a Senior Site Reliability Engineer to help us run one of the most exciting GPU clusters around—our Toronto datacenter packed with NVIDIA H100 and A100 GPUs, over 20PB of Ceph storage, terabit networking, and hundreds of servers. You'll be hands‑on with the full lifecycle of HPC infrastructure: planning, building, testing, deploying, and keeping everything running smoothly.

That means troubleshooting issues as they arise, monitoring performance, developing automation to make our lives easier, and working closely with engineering and science teams to ensure they have what they need. You'll also help us plan for future capacity and evaluate new technologies as we continue to scale.

• Manage and optimize HPC cluster operations
• Deploy and maintain infrastructure-as-code solutions
• Support ML/research teams with cluster usage optimization
• Operate, troubleshoot and optimize Ceph storage clusters
• Develop automation and tooling

• 5+ years of experience in SRE or HPC operations
• Proficiency in Linux systems administration (Ubuntu/Debian)
• Experience with Kubernetes and container orchestration
• Experience with Ceph >1PB deployments and maintenance
• Knowledge of security best practices in multi-tenant environments
• Understanding of L2/L3 networking fundamentals
• Skilled in Python and Bash scripting

• Experience with infrastructure-as-code tools (Ansible/Terraform)
• Experience with Git Ops (Helm, ArgoCD)
• Strong grasp of RDMA, Infini Band, and GPUDirect technologies
• Familiarity with deep learning frameworks such as PyTorch and Tensor Flow
• Familiarity in at least one cloud platform: AWS, Azure or GCP

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Not Applicable

Full-time

Engineering and Information Technology

Industries

Hospitality, Food and Beverage Services, and Retail

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