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

- Cluster Deployment & Maintenance

- Install and manage Linux-based compute nodes
- Maintain job schedulers and resource managers
- Integrate monitoring tools (Prometheus, Grafana, Nagios)

- Performance Tuning & Optimization

- Benchmark workloads and tune for performance (e.g., MPI, CUDA, OpenMP)
- Optimize I/O and inter-node communication
- Ensure effective job execution and queue handling

- 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)

- 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

- 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

- 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

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📌 HPC Specialist (Ottawa)
🏢 Arcadion
📍 Ottawa