Software Engineer, Infrastructure

fal is a generative media ecosystem powering the next generation of AI products. The role involves building software and processes to manage a large fleet of GPU servers, including provisioning, health monitoring, and error recovery.

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
• 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)