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TAIRC

GPU Infrastructure Specialist

Niagara-on-the-Lake, ON, Canada

Volunteer

Within 25 km of St. Catharines · About 11.3 km from the city centre

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Job details

Job type: Volunteer
Apply by: Nov 25, 2026
Posted: Nov 4, 2026

Original job description

Home/Careers/GPU Infrastructure Specialist

Infrastructure & Compute

GPU Infrastructure Specialist

These specialists focus on GPUs and hardware accelerators used for AI workloads.

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Overview

These specialists focus on GPUs and hardware accelerators used for AI workloads.

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.

Qualifications

Degree in electrical engineering or computer science.
Experience with GPU architecture, CUDA programming, and hardware monitoring tools.

Equal opportunity

TAIRC evaluates candidates using role-related evidence and documented review criteria. Employment decisions must not be based on protected personal characteristics.

Engagement pathways and compensation status

TAIRC is currently building its funding base. Opportunities identified as volunteer or unpaid do not provide compensation at this stage. Any future paid appointment would require available funding, organizational approval, applicable legal compliance, and a separate written agreement. Participation does not guarantee future employment or compensation.

Volunteer contribution interest may be reviewed only as a voluntary, scoped pathway.
Educational internship interest requires separate supervision, educational purpose, and legal review.
Advisory expressions of interest are not board or formal advisory appointments.
Future compensated employment is contingent on funding, approval, legal compliance, and a separate written offer.

Accessibility and accommodations

For an accommodation or alternate submission format, contact hr@tairc.com. The application form does not request medical documentation or sensitive identity documents.

Posting information

Department Infrastructure & Compute

Public role ID TAIRC-ROLE-039

Status Open

Location, employment type, workplace type, compensation, sponsorship policy, posted date, and closing date are omitted unless HR has entered approved factual values.

Recruitment privacy

Application data is used for recruitment review, stored with restricted access, and handled under the recruitment privacy and retention policy.

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More about this job

Responsibilities

Set up, configure, and maintain GPU-based servers, and optimize GPU utilization through multi-GPU training strategies, memory management, and load balancing. Advise researchers on hardware requirements for large-scale experiments and monitor hardware health, replacing components as needed.

Requirements

A degree in electrical engineering or computer science is required. Candidates should have experience with GPU architecture, CUDA programming, and hardware monitoring tools.

Skills

GPU Cluster Management
GPU Server Configuration
GPU Utilization Optimization
Multi-GPU Training
Memory Management
Load Balancing
Researcher Collaboration
Hardware Requirements Assessment
Hardware Monitoring
Hardware Reliability
GPU Architecture
CUDA Programming

Visa sponsorship

Not detected in the job text

Keywords

GPU Infrastructure
GPU Clusters
GPU-Based Servers
Hardware Accelerators
AI Workloads
GPU Utilization
Multi-GPU Training
Memory Management
Load Balancing
GPU Architecture
CUDA Programming
Hardware Monitoring Tools
Hardware Reliability
Electrical Engineering
Computer Science
Large-Scale Experiments
Research Services

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