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** - 3+ years experience managing bare-metal and cloud based 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) **Compensation** - $180,000-250,000 plus equity + benefits **Location** - San Francisco, CA **What we offer at fal** - Interesting and challenging work - A lot of learning and growth opportunities - We are offering relocation assistance to San Francisco. - We offer relocation assistance to San Francisco. - Health, dental, and vision insurance (US) - Regular team events and offsites