Senior GPU Infrastructure Engineer

Job not on LinkedIn

🕒 May 18

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 23%

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.

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decircle

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2019

📣 Marketing

📦 Logistics

💼 Consulting

Marketing • Logistics • Consulting

Decircle is a talent partner specializing in staffing and recruiting for decentralized organizations and projects related to Web3. As a boutique recruitment agency, Decircle focuses on identifying and attracting talent in the blockchain and Web3 sectors, fostering connections within the community of decentralization enthusiasts and guiding them in finding their roles in the evolving decentralized landscape.

📋 Description

• Help build and scale Hyperbolic's GPU Cloud Marketplace • Build a multi-tenancy provisioning and virtualization solution • Transform raw GPUs from diverse global suppliers into a programmable, orchestrated pool • Serve thousands of AI developers and researchers • Work at the cutting edge of cloud infrastructure • Build the core orchestration layer that enables the platform to deliver up to 75% cost savings compared to traditional cloud providers

🎯 Requirements

• Deep understanding of bare-metal provisioning and lifecycle management, including IPMI/Redfish, BMC-based remote management, PXE boot, and automated OS deployment workflows • Deep understanding of GPU scheduling and orchestration, including GPU type awareness, memory management, topology considerations, placement strategies for multi-GPU jobs, and fragmentation minimization • Strong infrastructure and DevOps engineering skills with proficiency in Terraform or Pulumi, CI/CD for infrastructure, secrets management, configuration management, and observability stack implementation • Experience with storage and data infrastructure for AI/ML workloads, including object storage, high-IOPS block storage, and distributed file systems for training data and checkpoints • Proficiency with API design and cloud-init for automated provisioning and configuration • Solid understanding of GPU architecture, CUDA, and GPU compute optimization • Highly collaborative team player with excellent communication skills across technical and non-technical stakeholders • Proven ability to work effectively with hardware vendors and vendor engineering teams to troubleshoot issues and optimize integrations • Experience building and scaling cloud infrastructure or distributed systems in production environments