You are a hands-on engineer who builds the software and processes that keep a large fleet of GPU servers healthy and productive. You write systems and tooling for managing 1000s of servers including provisioning, health monitoring, error detection, and recovery — and when something breaks that automation can’t fix, you drive resolution with partners.
Key responsibilities
- Build and maintain Python fleet tracking system that manages the full lifecycle of servers including contracting and procurement, target use, pricing, availability, health, RMAs, etc
- Build server management tooling that automates provisioning, health checks, GPU diagnostics, recovery and alerting
- Create and maintain metrics, dashboards, and alerting for hardware health across the fleet (GPU errors, disk failures, network issues, thermals)
- Leverage AI to an extreme level to build tools and automate alerting and recovery
- Implement and enforce OS-level security: hardening baselines, SELinux/AppArmor policies, SSH key management, vulnerability scanning, and compliance automation
- Manage and optimize distributed and local storage systems supporting model weights, checkpoints, and ephemeral scratch: NVMe arrays, NFS, parallel file systems, and object storage
- Tune Linux systems for AI workloads: kernel parameters, NUMA topology, CPU pinning, hugepages, I/O schedulers, and GPU driver stack optimization (NVIDIA drivers, CUDA, container runtimes)
- Develop a suite of automated error detection and recovery processes
- Work with partners to solve technical issues
Requirements
- 5+ years experience managing bare-metal and VM server fleets at scale (100+ nodes)
- Strong software engineering skills in Python; you write production tooling, not scripts
- Deep Linux systems knowledge: boot process, kernel tuning, networking, storage, systemd, cgroups, namespaces, performance profiling
- Strong experience with configuration management and infrastructure-as-code: Ansible, Terraform, cloud-init
- Solid understanding of storage technologies: LVM, RAID, NVMe, NFS, Lustre or GPFS, and Linux I/O stack tuning
- Familiarity with hardware diagnostics and failure modes (GPUs, NVMe, NICs, memory)
- Experience building internal tools or dashboards for infrastructure visibility
- Excellent communication and ability to drive technical decisions across teams
- Self-starter who executes quickly, takes ownership, and constantly seeks improvement
Nice to have
- Familiarity with network configuration and diagnostics (VLAN, VXLAN, ECMP, BGP, tcpdump)
- Experience with NVIDIA GPU infrastructure: driver management, health monitoring, DCGM, NVLink/NVSwitch diagnostics, RDMA, InfiniBand/RoCEv2
- Experience with AMD GPUs
- Experience with bare metal and VM provisioning (PXE/iPXE, Kickstart, libvirt, Qemu/KVM)
- Experience with compliance frameworks relevant to cloud providers (SOC 2, ISO 27001)
Location
What we offer at fal
- Interesting and challenging work
- A lot of learning and growth opportunities
- Regular team events and offsites
