About the Role Our client, a leading research institution, is seeking an experienced AI Infrastructure Engineer to manage and optimize their High-Performance Computing (HPC) environment dedicated to AI workloads. This hybrid role involves regular collaboration at our Kimberley facility, combined with remote work flexibility. You will be responsible for the design, implementation, and maintenance of scalable, high-performance computing infrastructure required for large-scale AI model training and inference. This is a critical role for enabling groundbreaking AI research and development, requiring deep expertise in distributed systems, networking, and hardware acceleration.
Key Responsibilities Design, build, and maintain scalable HPC infrastructure for AI workloads, including GPU clusters and distributed storage systems.
Optimize system performance for AI training and inference tasks, focusing on compute, memory, and network bottlenecks.
Manage and deploy AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Horovod) on the HPC cluster.
Implement and manage containerization technologies (e.g., Docker, Kubernetes) for AI workloads.
Monitor system health, performance, and resource utilization, proactively addressing issues.
Automate infrastructure deployment, configuration, and management using scripting and infrastructure-as-code tools.
Collaborate with AI researchers and engineers to understand their infrastructure needs and provide support.
Ensure the security and reliability of the AI infrastructure.
Stay up-to-date with the latest advancements in HPC, AI hardware (GPUs, TPUs), and distributed systems.




Develop and maintain documentation for infrastructure setup, usage, and troubleshooting.
Requirements Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Minimum of 6 years of experience in systems engineering, infrastructure management, or DevOps, with a strong focus on HPC or large-scale distributed systems.
Proven experience managing GPU clusters and optimizing them for AI/ML workloads.
Strong understanding of Linux operating systems, networking protocols, and storage solutions.
Hands-on experience with container orchestration platforms like Kubernetes.
Proficiency in scripting languages such as Python, Bash, or PowerShell.
Familiarity with AI/ML frameworks and libraries.
Experience with infrastructure-as-code tools (e.g., Terraform, Ansible) is a plus.
Excellent troubleshooting, problem-solving, and analytical skills.
Strong communication and collaboration abilities.
Ability to work effectively in a hybrid environment, commuting to Kimberley as needed.
Benefits Our client offers a market-competitive salary, comprehensive medical and retirement benefits.
We provide excellent opportunities for professional development, including access to cutting-edge technologies and training programs.
The hybrid work model offers flexibility and supports work-life balance.
You will be part of a dynamic research environment in our Kimberley facility, working on projects that are at the forefront of AI innovation.
This role offers significant career growth potential and the chance to make a substantial impact on the future of AI research infrastructure.

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📌 AI Infrastructure Engineer - High-Performance Computing (HPC) (British Columbia)
🏢 Placements24
📍 British Columbia