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GPU Infrastructure Specialist

  • Niagara-on-the-Lake, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job description

TAIRC seeks a GPU Infrastructure Specialist to support GPUs and hardware accelerators used for AI workloads. The role manages GPU clusters, optimizes GPU utilization, advises researchers on hardware requirements, and ensures hardware reliability.

Responsibilities

  • Manage GPU clusters: Set up, configure, and maintain GPU-based servers
  • Optimize GPU utilization: Implement strategies for multi-GPU training, memory management, and load balancing
  • Collaborate with researchers: Provide advice on hardware requirements for large-scale experiments
  • Ensure reliability: Monitor hardware health and replace components as needed
More about this job

Responsibilities

Manage and maintain GPU-based servers and clusters, optimizing utilization through multi-GPU training strategies, memory management, and load balancing. Advise researchers on hardware needs for large-scale experiments and monitor hardware health, replacing components as needed.

Requirements

The role calls for experience managing GPU clusters and supporting hardware accelerators for AI workloads. It also requires the ability to optimize GPU utilization, advise researchers on hardware requirements, and maintain hardware reliability.

Skills

  • GPU Cluster Management
  • GPU Server Configuration
  • GPU Utilization Optimization
  • Multi-GPU Training
  • Memory Management
  • Load Balancing
  • Hardware Requirements Advising
  • Hardware Health Monitoring
  • Hardware Reliability
  • Component Replacement

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Engineering
  • Science & Research

Keywords

  • GPU
  • Hardware Accelerators
  • AI Workloads
  • GPU Clusters
  • GPU-Based Servers
  • GPU Utilization
  • Multi-GPU Training
  • Memory Management
  • Load Balancing
  • Large-Scale Experiments
  • Hardware Requirements
  • Hardware Health
  • Hardware Reliability
  • Component Replacement

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