HPC Infrastructure Engineer – GPU Clusters

Job not on LinkedIn

🔥 1 minute ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

ElevenLabs

WebsiteLinkedInAll Job Openings

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 problems involving stragglers, degraded links, thermal issues, and faulty GPUs • Evaluate rented GPU capacity by benchmarking providers, validating capacity, and enforcing SLAs • Perform hands-on hardware work, including racking, cabling, and diagnostics • Coordinate with datacenter staff and vendors • Maintain cluster security through access control, network isolation, and secrets management • Work directly with researchers to improve training throughput and researcher velocity

🎯 Requirements

• Production experience running large-scale Linux server or GPU environments • Strong knowledge of NVIDIA 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 • Proficiency in Python and/or Bash automation • Experience with infrastructure-as-code tools such as 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) • Power and cooling awareness 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 social travel stipend to meet colleagues • Annual company offsite • Monthly co-working stipend for employees not near a main hub • Remote work flexibility • Ability to work from offices in London, New York, San Francisco, or Warsaw