Senior GPU Infrastructure Engineer

Hyperbolic Labs

$130K — $180K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in infrastructure engineering or related field
  • Expertise in bare-metal provisioning and lifecycle management methodologies
  • Proficient in Terraform or Pulumi, with strong DevOps skills
  • Experience with data infrastructures tailored for AI/ML workloads
  • Solid knowledge of GPU architectures and CUDA for performance optimization
  • Exceptional collaboration and communication skills with a wide range of stakeholders
  • Hands-on experience with vendor management and troubleshooting hardware issues

Responsibilities

  • Design and implement a multi-tenancy provisioning and virtualization solution for GPU Cloud Marketplace
  • Transform raw GPUs from multiple suppliers into a programmable orchestrated pool
  • Build core orchestration layers to maximize efficiency and reduce costs
  • Optimize GPU scheduling, memory management, and topology for multi-GPU tasks
  • Integrate observability tools for monitoring and managing infrastructure health
  • Collaborate with development teams and external vendors to resolve issues and optimize processes

Benefits

  • Work at the forefront of cloud infrastructure technology
  • Join a team focused on cutting-edge AI and GPU applications
  • Opportunity to make a significant impact in a foundational engineering role
  • Contribute to a cost-saving solution compared to traditional cloud offerings
  • Engage with a collaborative and supportive team environment
Full Job Description
About the Role

We're seeking a Senior Infrastructure Engineer to help build and scale Hyperbolic's GPU Cloud Marketplace, by building a multi-tenancy provisioning and virtualization solution. This is a foundational role where you'll be responsible for transforming raw GPUs from diverse global suppliers into a programmable, orchestrated pool that serves thousands of AI developers and researchers. You'll work at the cutting edge of cloud infrastructure, building the core orchestration layer that enables our platform to deliver up to 75% cost savings compared to traditional cloud providers.

Who You Are
  • 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


Preferred Qualifications
  • Familiarity with high-performance networking technologies such as InfiniBand and RoCE (RDMA over Converged Ethernet)
  • Experience with distributed storage systems such as Ceph, Weka, or VAST Data

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