Senior SRE - AI Infrastructure

Keen to join a company that champions growth and development?

Join a seed-stage AI infrastructure company building large-scale training and inference platforms that were previously accessible only to hyperscalers. The business began with a single managed GPU cluster that quickly reached capacity and has since expanded into a global platform spanning infrastructure, networking, and orchestration.

Don’t miss out on this exciting opportunity and apply today!

Responsibilities:

• Design, deploy, and maintain large-scale GPU clusters (H100/H200/B200) for training and inference workloads.
• Build automation pipelines for provisioning, scaling, and monitoring compute resources across Slurm and Kubernetes environments.
• Develop observability, alerting, and auto-healing systems for high-availability GPU workloads.
• Collaborate with ML, networking, and platform teams to optimise resource scheduling, GPU utilisation, and data flow.
• Implement infrastructure-as-code, CI/CD pipelines, and reliability standards across thousands of nodes.
• Diagnose performance bottlenecks and drive continuous improvements in reliability, latency, and throughput.
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Skills / Must Have:

• 7+ years of experience in SRE, DevOps, or Infrastructure Engineering roles supporting large-scale compute environments.
• Strong hands-on experience with Kubernetes and Slurm for cluster orchestration and workload management.
• Deep knowledge of Linux systems, networking, and GPU infrastructure (NVIDIA H100/H200/B200 preferred).
• Proficiency in Python, Go, or Bash for automation, tooling, and performance tuning.
• Experience with observability stacks (Prometheus, Grafana, Loki) and incident response frameworks.
• Familiarity with high-performance computing (HPC) or AI/ML training infrastructure at scale.
• Background in reliability engineering, distributed systems, or hardware acceleration environments is a strong plus.

Benefits:

• IPO Equity
• 10% comapny bonus
• 401K 4% match

Salary:

• $250,000 gross per year +