HPC Specialist

Arcadion; Ottawa; On-site; CAD 80,000 - 110,000; Full time

Job summary

Arcadion is seeking an HPC Specialist in Ottawa, Ontario, responsible for designing and optimizing high-performance computing systems for various applications, including scientific research and AI/ML workloads. The ideal candidate will have 3-7 years of relevant experience, familiar with tools like Slurm and NVIDIA GPUs. A degree in Computer Science or Engineering is required, along with certifications in HPC. This role offers opportunities to work on cutting-edge computing projects in a dynamic environment.

Qualifications

• 3-7 years of experience in HPC environments.
• Experience supporting AI/ML teams is a major asset.
• Certifications such as AWS Certified HPC Specialist or Linux+ are preferred.

Responsibilities

• Design and deploy scalable HPC clusters.
• Manage Linux-based compute nodes and job schedulers.
• Optimize performance and manage AI pipelines.

Skills

HPC cluster design

Linux management

Performance tuning

Cloud HPC integration

AI/ML workload support

Security best practices

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

Slurm

PBS

CUDA

TensorFlow

Kubernetes

AWS ParallelCluster

Job description

HPC Specialist – Role Overview

Arca dion is seeking an HPC (High-Performance Computing) Specialist responsible for the design, deployment, optimization, and management of high-performance computing systems, often used in scientific research, engineering simulations, AI/ML workloads, and large-scale data analytics.

Core Responsibilities

1. Architecture & System Design
   • Design scalable HPC clusters (on-prem, cloud, or hybrid)
   • Choose appropriate CPUs, GPUs, interconnects (e.g., InfiniBand), and storage
   • Configure Slurm, PBS, or OpenHPC job schedulers
2. Cluster Deployment & Maintenance
   • Install and manage Linux-based compute nodes
   • Maintain job schedulers and resource managers
   • Integrate monitoring tools (Prometheus, Grafana, Nagios)
3. Performance Tuning & Optimization
   • Benchmark workloads and tune for performance (e.g., MPI, CUDA, OpenMP)
   • Optimize I/O and inter-node communication
   • Ensure efficient job execution and queue handling
4. Cloud & Hybrid HPC Integration
   • Deploy and manage cloud-based HPC environments (Azure CycleCloud, AWS ParallelCluster, Google Cloud HPC Toolkit)
   • Optimize workload portability and orchestration (e.g., Singularity, Kubernetes with KubeFlow or Volcano)
5. AI/ML & GPU Workload Support
   • Manage AI pipelines that require HPC acceleration (e.g., LLM training)
   • Optimize GPU usage (NVIDIA A100/H100, AMD MI300)
   • Interface with TensorFlow, PyTorch, and HPCML tools
6. Security & Compliance
   • Implement security best practices for multi-user environments
   • Support data governance for sensitive or regulated workloads
   • Maintain audit trails and role-based access control
7. User & Application Support
   • Assist researchers and data scientists with job submissions and optimizationDevelop documentation, training materials, and run code validation sessions

Technical Skills & Tools

• Schedulers: Slurm, PBS, Torque, LSF
• HPC OS & Config: RHEL/CentOS, Rocky, Ubuntu Server
• HPC File Systems: Lustre, BeeGFS, GPFS
• Parallel Computing: MPI, OpenMP, CUDA
• Monitoring/Telemetry: Prometheus, Grafana, Ganglia
• Cloud HPC: AWS HPC, Azure CycleCloud, GCP HPC Toolkit
• Containers: Singularity, Apptainer, Docker, Kubernetes
• AI/ML Support: PyTorch, TensorFlow, Horovod, MLFlow
• DevOps Tools: Ansible, Terraform, Git, Jenkins

Qualifications

• Bachelor’s or Master’s in Computer Science, Engineering, Physics, or a related technical field
• 3–7 years of experience in HPC environments
• Experience supporting AI/ML teams is a major asset
• Certifications: NVIDIA DLI, AWS Certified HPC Specialist, Linux+ or RHCE