Senior GPU Infrastructure Engineer

Job not on LinkedIn

🕒 May 18

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

👷 Infrastructure Engineer

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote 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

decircle

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2019

We partner with disruptive organizations to help identify and attract talent. A boutique recruitment agency that focuses on blockchain and web3. We enjoy networking with Web3 and decentralization enthusiasts and help them find their place in the decentralized world.

📋 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