Member of Technical Staff, GPU Infrastructure

📋 Description

• Deploy and operate GPU Kubernetes clusters across clouds, and bring up new hardware generations and
• Work with cloud providers and hardware partners on reliability, performance, and cost, including
• Automate node, GPU, and fabric fault detection and remediation so most faults are fixed without a
• Improve fleet utilization, track cost, and cut the time it takes to get a faulty node back into
• Troubleshoot production failures and performance problems, and leave the system easier to operate

🎯 Requirements

• Run GPU Kubernetes clusters with thousands of GPUs for ML or HPC workloads.
• Debugged Linux, networking, and performance problems. Familiarity with RDMA, NCCL, or accelerator
• Written software in Python or Go. You would rather extend a solid open-source project than rebuild
• Worked with researchers, ML engineers, or another team whose goals were not identical to yours.
• Found a bottleneck, proposed a fix, and driven it in a fast-moving environment.

🎁 Benefits

• A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
• Full health and dental benefits, including a separate budget for mental health.
• RRSP matching, 401K, Pension Scheme.
• 100% Parental Leave top-up for up to 6 months, for either parent.
• Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace
• 6 weeks of paid vacation (30 working days!)