HPC Engineer

About this role

At Verda , we're building a full-stack AI cloud, covering everything from data centers and hardware to our own cloud platform that the world's leading AI teams use to do serious AI work. We strive to make a positive mark on the world through the infrastructure we build and give leading teams a service they can truly depend on. Headquartered in Helsinki, we operate globally with offices in London and San Francisco. Join Verda while it’s still being built - not once it’s finished.

Why Verda Cash and equity compensation along with various fringe benefits. Profitable operations with rapid, sustained growth. 30+ nationalities, with 6 different ones on the management team. A real chance to make an impact and work alongside world class engineers, researchers, and partners across the global AI ecosystem. Practicalities Work mode: Remote (EU) Level: Mid / Senior Employment type: Full time and permanent About the role GPUs only deliver value once they're wired into a cluster that researchers can actually train on.

As our HPC Engineer, you'll own the baremetal and virtualized clusters behind our AI cloud - from the InfiniBand fabric and shared filesystems up through the workload orchestration layer. You'll be the person who keeps large-scale GPU clusters healthy, performant, and ready for the next workload. Your responsibilities Administer baremetal GPU/HPC clusters end to end, from provisioning through day-two operations Administer virtualized clusters, including the hypervisor and GPU virtualization stack underneath them Design, deploy, and tune InfiniBand fabrics, including topology planning, subnet management, and performance validation Deploy and operate shared/parallel filesystems supporting training and inference workloads, balancing performance, capacity, and reliability Troubleshoot and resolve issues across the full fabric stack: fibers, transceivers, NICs, switches, drivers, and firmware Partner with remote-hands and data center teams to diagnose hardware faults and execute physical-layer fixes and cluster expansions Operate and tune Slurm (or equivalent) workload scheduling deployments used by customers and internal teams Keep issue tracking, IPAM, and DCIM records accurate as clusters are built, changed, and decommissioned Participate in on-call rotations and incident response for cluster-level issues Collaborate with platform, network, and storage teams to integrate new clusters into the broader AI cloud Your key competencies Solid Linux skills, with specialization in memory management, PCIE topologies and virtualization being a bonus Deep Infiniband knowledge, including fabric design, subnet management, and performance tuning Solid experience with IB clustering, troubleshooting/debugging, understanding the ecosystem of fibers+transceivers+NICs+switches and all the things that could possibly fail in them Experience about shared filesystems (e.g.