Staff HPC Systems Software Engineer (AI)

Location: UK

Company

Nscale provides GPU cloud infrastructure for AI start-ups and enterprise customers, focusing on high-performance, cost-effective, and sustainable AI computing.

What you will do

• Define the technical direction and architecture for a core HPC systems domain, including Slurm platform architecture, scheduler integrations, cluster lifecycle, workload environments, or service automation.
• Package, automate, and expose Slurm implementations as services while establishing maintainable lifecycle and operating models.
• Lead cross-team design across Slurm, Kubernetes-adjacent systems, infrastructure APIs, identity systems, and platform tooling.
• Create reusable automation, deployment patterns, modules, and reference implementations to reduce duplicated effort and technical divergence.
• Lead technically critical initiatives across 2–4 teams and contribute hands-on engineering to de-risk complex work.
• Improve the reliability, observability, supportability, and maintainability of GPU-backed HPC services.

Requirements

• Extensive experience designing and building production software and automation for HPC systems, especially Slurm-based environments.
• Strong experience writing maintainable, testable, and resilient software in Go, Python, or similar languages.
• Deep understanding of Slurm internals, scheduler behavior, cluster lifecycle concerns, and operational trade-offs.
• Practical experience with GPU-backed infrastructure and HPC networking, including InfiniBand, RoCE, RDMA, and performance-sensitive workloads.
• Experience integrating HPC systems with cloud-native platforms, APIs, or service delivery models.
• Strong technical judgment, communication skills, and the ability to align multiple teams without formal authority.

Nice to have

• Experience with other schedulers or batch systems such as Kueue.

Culture & Benefits

• Opportunity to shape operating standards for a next-generation AI cloud platform.
• Work on complex infrastructure challenges with ownership and direct technical impact.
• Contribute to scaling high-performance and sustainable data center operations.
• Inclusive workplace with support for accessibility and individual accommodation needs.