Senior HPC Engineer

About the role

ABOUT NEXGEN CLOUD

NexGen Cloud is a fast-growing GPU cloud and AI infrastructure business. We’re the company behind Hyperstack — a self-serve, on-demand cloud platform built for high-performance AI, HPC, and compute-heavy workloads. Powered by 100% renewable energy and NVIDIA architecture, Hyperstack gives teams from AI startups to enterprise the compute they need, without the cost or complexity of legacy cloud.

We move fast, solve hard problems, and build things that matter. If you want ownership, real impact, and a front-row seat to one of the most consequential infrastructure shifts of the decade — this is the place.

THE ROLE: HPC ENGINEER

We’re deploying more large-scale NVIDIA GPU clusters connected by InfiniBand, and the gap between a cluster that’s built and one that delivers its expected training performance is where customer experience is won or lost. We need an HPC Engineer to close that gap: validating and tuning clusters before handover, then owning the HPC layer in production. This is a UK-based remote role, reporting to the Head of Infrastructure.

This is a role for someone who won’t sign off a cluster that isn’t right, who follows a problem across GPUs, fabric, storage and software until it’s fixed rather than handing it off, and who is comfortable owning outcomes without heavy oversight.

WHAT YOU’LL BE DOING

Rather than a checklist, here’s what success in this role actually looks like:

- Own cluster performance from acceptance to production, running burn-in, health checks and NCCL, HPL and storage benchmarks against agreed criteria, and resolving underperformance before a cluster reaches the customer.

- Collaborate closely with Deployment Solution Architects, Network Engineers, Validation, Customer Support and vendors including NVIDIA and OEMs to resolve issues quickly and feed production learning back into design.

- Run the production HPC layer day to day: Slurm, GPU drivers and the CUDA stack, InfiniBand fabrics (subnet management, monitoring, firmware) and the parallel storage clusters depend on.

- Tune clusters for AI training and HPC workloads, from NCCL settings and GPUDirect RDMA to topology-aware scheduling and storage throughput.

- Build GPU, fabric and job-level monitoring that catches faults before customers notice, and lead incident response from Xid errors and fabric degradation through to root cause.

- Automate provisioning, configuration and validation with infrastructure-as-code and Git-based workflows, building a standard, repeatable validation suite for each GPU platform and fabric type.

- Turn incident learning into automated checks, runbooks and lasting fixes, and become the go-to engineer for HPC and InfiniBand across the business.

ABOUT YOU

We care more about how you think and work than a perfect CV. You’ll likely bring a combination of the following:

Essential:

- Hands-on experience operating NVIDIA GPU infrastructure at scale, including drivers, CUDA, DCGM and diagnosing GPU hardware faults.