Software Engineer, AI Infra & GPU Fleet Orchestration

Kindredventures; United States; Remote; USD 12,756 - 19,134; Full time

Benefits offered by this job

Interesting and challenging work

Learning and growth opportunities

Regular team events and offsites

Job summary

fal is building the generative media ecosystem and is hiring a hands-on engineer to keep a large fleet of GPU servers healthy and productive. You will write systems for provisioning, health monitoring, error detection, and recovery, collaborating with partners to resolve issues at scale.

You will develop Python tooling for fleet lifecycle management, implement OS-level security, and optimize storage and GPU driver stacks to support AI workloads.

Qualifications

• 3+ years experience managing bare-metal and cloud based server fleets at scale (100+ nodes).
• Strong software engineering skills in Python; 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.

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 ephemerals 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

Skills

Python

Linux

Ansible

Terraform

cloud-init

NVMe

Lustre

Dashboards

Communication

Self-starter

Tools

NVIDIA drivers

CUDA

container runtimes

Job description

fal is building the generative media ecosystem and is hiring a hands-on engineer to keep a large fleet of GPU servers healthy and productive. You will write systems for provisioning, health monitoring, error detection, and recovery, collaborating with partners to resolve issues at scale.

You will develop Python tooling for fleet lifecycle management, implement OS-level security, and optimize storage and GPU driver stacks to support AI workloads.