GPU Cloud Infra Architect: Multi-Tenancy & Scheduling

Deciml; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Hyperbolic Labs is building a foundational infrastructure team to provision and virtualize GPU resources from global suppliers into a scalable, programmable cloud marketplace. The role focuses on bare-metal provisioning, scheduling, storage, and networking, delivering a robust platform for thousands of AI researchers.

You will work hands-on with IPMI/Redfish, PXE, and automated OS deployment, while collaborating across hardware vendors and software teams to optimise integrations and

Qualifications

• Deep understanding of bare-metal provisioning and lifecycle management.
• Deep understanding of GPU scheduling and orchestration, including placement strategies for multi-GPU jobs.
• Strong infrastructure and DevOps engineering skills: 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: object storage, high-IOPS block storage, and distributed file systems.
• Solid understanding of GPU architecture, CUDA, and GPU compute optimisation.
• Proven experience building and scaling cloud infrastructure or distributed systems in production environments.
• Excellent communication skills across technical and non-technical stakeholders.

Responsibilities

• Build and scale the GPU Cloud Marketplace by designing multi-tenancy provisioning and virtualisation solutions.
• Manage bare-metal provisioning and lifecycle management: IPMI/Redfish, BMC-based remote management, PXE boot, automated OS deployment.
• Design and implement GPU scheduling and orchestration: GPU type awareness, memory management, topology considerations, placement strategies for multi-GPU jobs, fragmentation minimisation.
• Build and maintain infrastructure automation using Terraform or Pulumi, CI/CD pipelines, secrets management, configuration management, and observability stacks.
• Design storage and data infrastructure for AI/ML workloads: object storage, high-IOPS block storage, distributed file systems for training data and checkpoints.
• Implement API design and cloud-init for automated provisioning and configuration.
• Work with hardware vendors and vendor engineering teams to troubleshoot issues and optimise integrations.

Skills

Bare-metal provisioning

GPU scheduling

Communication

Tools

Terraform

Pulumi

CI/CD pipelines

Observability stack

Kubernetes GPU operators

Slurm

Ray

Job description

Hyperbolic Labs is building a foundational infrastructure team to provision and virtualize GPU resources from global suppliers into a scalable, programmable cloud marketplace. The role focuses on bare-metal provisioning, scheduling, storage, and networking, delivering a robust platform for thousands of AI researchers.

You will work hands-on with IPMI/Redfish, PXE, and automated OS deployment, while collaborating across hardware vendors and software teams to optimise integrations and