HPC Infrastructure Engineer – GPU Clusters

Job not on LinkedIn

🕒 September 3

🌐 United States, Bulgaria, +2 more countries – Remote

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⏰ Full Time

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

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Logo of ElevenLabs

ElevenLabs

1 - 10 employees

🤖 Artificial Intelligence

📱 Media

💰 $19M Series A on 2023-06

Artificial Intelligence • Media

ElevenLabs is a research lab dedicated to exploring new frontiers in voice generation. Their mission focuses on making content universally accessible in any language and voice. Through innovative research and deployment of novel methods in voice AI, ElevenLabs aims to enhance the enjoyment of content for diverse audiences and viewers.

📋 Description

• Operate and improve the GPU fleet end to end, including provisioning, scheduling, monitoring, upgrades, and capacity planning • Build automation for node health checks, automated draining and remediation, and burn-in pipelines • Own the infrastructure stack beneath training code, including OS images, NVIDIA drivers, CUDA, container runtimes, NCCL, and InfiniBand/RoCE networking • Run and tune job scheduling with Slurm or similar systems • Build and maintain high-performance storage for datasets and checkpoints • Investigate and resolve performance issues involving stragglers, degraded links, thermal issues, and faulty GPUs • Evaluate rented GPU capacity, benchmark it, validate it, and hold providers to SLAs • Perform hands-on hardware work including racking, cabling, diagnostics, and coordination with datacenter staff and vendors • Maintain cluster security through access control, network isolation, and secrets management

🎯 Requirements

• Experience running large-scale Linux server or GPU environments in production • Strong knowledge of the NVIDIA stack, including drivers, CUDA, NCCL, and DCGM, or deep systems experience with ability to learn hardware stacks quickly • Experience with bare-metal environments, server hardware, and high-speed networking • Python and/or Bash automation skills • Experience with Ansible or Terraform • Ability to analyze metrics, logs, and PromQL • Experience supporting ML training workloads from the infrastructure side (nice to have) • Experience evaluating and working with GPU cloud providers (nice to have) • Experience with parallel filesystems such as WEKA or VAST, or large-scale object storage (nice to have) • Experience with BMC/IPMI/Redfish automation and PXE provisioning at scale (nice to have) • Awareness of power and cooling for dense GPU deployments (nice to have) • Willingness to perform datacenter trips and hands-on hardware work

🏖️ Benefits

• Annual discretionary professional development stipend • Annual discretionary stipend for meeting colleagues • Annual company offsite • Monthly co-working stipend • Remote work flexibility • Option to work from offices in London, New York, San Francisco, and Warsaw

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