Infrastructure Engineer, AI Hardware Platform & Equity

Acceler8 Talent; San Francisco (CA); On-site; USD 150,000 - 390,000; Full time

Job summary

Acceler8 Talent in San Francisco is seeking a Member of Technical Staff, Infrastructure to build and operate the cluster infrastructure behind our AI platform. You will determine how new accelerator hardware is brought online, how compute fleets are provisioned, and how production inference systems remain reliable at scale.

You will deploy production clusters across accelerator architectures, automate provisioning and fleet lifecycle, improve scheduling and resource utilization, and build

Qualifications

• Experience in infrastructure, platform engineering, cluster engineering, SRE, or HPC.
• Strong Linux systems knowledge and production debugging experience.
• Experience operating Kubernetes, Slurm, Nomad, or similar orchestration systems.
• Infrastructure automation experience using Python, Go, Terraform, or Ansible.
• Experience with GPU or accelerator infrastructure, including drivers, firmware, CUDA, or ROCm.
• A track record of building observable, recoverable, and reliable production systems.

Responsibilities

• Deploy production clusters across different accelerator architectures.
• Automate bare-metal provisioning, validation, upgrades, and fleet lifecycle management.
• Improve cluster scheduling, resource utilization, isolation, and capacity management.
• Build observability systems for faster debugging, incident response, and recovery.
• Make new accelerators production-ready across drivers, firmware, networking, and orchestration.
• Partner with runtime, compiler, distributed-systems, networking, and hardware engineers.

Skills

Linux systems

Production debugging

Observability

Cloud platforms

Tools

Kubernetes

Slurm

Nomad

Python

Go

Terraform

Ansible

CUDA

GPU drivers

Job description

Acceler8 Talent in San Francisco is seeking a Member of Technical Staff, Infrastructure to build and operate the cluster infrastructure behind our AI platform. You will determine how new accelerator hardware is brought online, how compute fleets are provisioned, and how production inference systems remain reliable at scale.

You will deploy production clusters across accelerator architectures, automate provisioning and fleet lifecycle, improve scheduling and resource utilization, and build