HPC Infrastructure Engineer

A seed-stage neocloud company is hiring an HPC Infrastructure Engineer to build and operate the foundation of its GPU and TPU cloud. You'll work across bare-metal systems, high-speed networking, cluster scheduling, storage, automation, and reliability, turning a large fleet of accelerators into a high-performance, dependable computing platform for customers. This is a hands‑on role for someone who loves working across hardware and software, diagnosing tough performance problems, and building infrastructure from the ground up.

What You'll Do

• Design, deploy, and operate production TPU clusters
• Provision and manage Linux-based bare-metal servers at scale
• Build automated workflows for server installation, configuration, upgrades, and recovery
• Deploy and operate cluster schedulers such as Slurm or Kubernetes
• Integrate high-performance networking using InfiniBand or RoCE/RDMA
• Build and operate high‑throughput storage for distributed AI workloads
• Monitor cluster health, accelerator utilization, network performance, storage performance, and job reliability
• Diagnose failures across GPUs, servers, firmware, networks, storage, schedulers, and customer workloads
• Improve cluster utilization, training performance, fault tolerance, and recovery time
• Establish production practices for change management, incident response, capacity management, and operational readiness
• Partner with data-center, network, platform, security, and customer-facing teams to launch new capacity
• Evaluate and manage infrastructure vendors, hardware suppliers, and technical partners
• Participate in an on-call rotation as the production platform grows

What We're Looking For

• Experience building or operating production HPC, supercomputing, or large-scale bare-metal infrastructure
• Strong Linux systems-engineering and debugging skills
• Experience automating physical server provisioning and configuration
• Experience with Slurm, Kubernetes, or another distributed workload scheduler
• Understanding of high-performance networking, distributed storage, and accelerator-based computing
• Experience with monitoring, incident response, performance analysis, and production reliability
• Proficiency in Python, Go, Bash, or another infrastructure automation language
• Ability to diagnose problems across layers rather than treating compute, networking, storage, and software as separate systems
• Comfort working directly with hardware, vendors, data-center teams, and customers in an early-stage environment

Especially Valuable

• NVIDIA GPU clusters, TPU systems, CUDA, NCCL, or collective communications
• InfiniBand, RoCEv2, RDMA, GPUDirect, or high-performance Ethernet
• Slurm administration and scheduling optimization
• Kubernetes for accelerator workloads
• PXE, Redfish, IPMI, BMCs, and bare-metal lifecycle management
• Ansible, Terraform, or other infrastructure-as-code systems
• Lustre, Spectrum Scale/GPFS, Ceph, BeeGFS, or other distributed storage systems
• Prometheus, Grafana, OpenTelemetry, or infrastructure observability tooling
• GPU health monitoring, firmware management, and hardware failure diagnosis
• Distributed AI training and inference workloads
• Performance benchmarking and optimization across compute, network, and storage
• Experience at a neocloud, hyperscaler, AI lab, national laboratory, or HPC center