HPC Engineer : AI Workloads & Infrastructure (Remote)

Role Overview

About iVedha

iVedha is a leading provider of cloud and managed services, helping enterprises modernize their IT infrastructure and accelerate digital transformation. Be part of the Canada’s next-generation sovereign AI infrastructure team, delivering high-performance computing solutions for AI, ML, and scientific workloads. Our mission is to empower innovators with secure, scalable, and sustainable compute platforms.

Role Overview

We are seeking an HPC Engineer to join our operational team supporting AI workloads in a high-performance computing environment. This role focuses on building and managing HPC compute nodes, deploying Kubernetes clusters, and orchestrating bare-metal and virtualized environments. You will also work with advanced storage technologies such as VAST Data and MooseFS, ensuring seamless integration with GPU-accelerated infrastructure.

Requirements

Required Skills & Experience

• 4+ years in HPC engineering, systems administration, or AI infrastructure roles.
• Strong experience with Linux (RHEL/CentOS/Ubuntu) in HPC environments.
• Hands-on experience with Kubernetes, Docker, and container orchestration for AI workloads.
• Familiarity with GPU clusters, CUDA, NCCL and NVIDIA ecosystem tools.
• Knowledge of high-speed interconnects (InfiniBand, RoCE) and networking for HPC.
• Experience with parallel/distributed file systems (VAST, MooseFS, Lustre, GPFS).
• Proficiency in automation and scripting (Python, Bash, Ansible).
• Understanding of job schedulers (Slurm, PBS, Torque) and workload optimization.

Nice-to-Have

• Experience with cloud HPC platforms (Azure HPC, AWS ParallelCluster, or similar).
• Familiarity with AI/ML frameworks (PyTorch, TensorFlow) and MLOps pipelines.
• Exposure to observability tools (Prometheus, Grafana) for HPC environments.