HPC Engineer --AI Workloads & Infrastructure (Remote)
About the role
iVedha is seeking an HPC Engineer to join their operational team focused on supporting AI workloads in a high-performance computing environment. The role involves building and managing HPC compute nodes, deploying Kubernetes clusters, and orchestrating both bare-metal and virtualized environments. The engineer will also work with advanced storage technologies and ensure integration with GPU-accelerated infrastructure. Key responsibilities include managing Linux systems, container orchestration, networking, automation, and workload optimization within HPC environments. iVedha is a leading provider of cloud and managed services, supporting enterprises in modernizing IT infrastructure and accelerating digital transformation, with a focus on secure and scalable compute platforms for AI, ML, and scientific workloads.
Must have
- 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.
Technologies
- Ansible
- AWS
- Azure
- Bash
- CUDA
- Docker
- Grafana
- HPC
- Kubernetes
- Linux
- Machine Learning
- MLOps
- Observability
- Prometheus
- Python
- PyTorch
- RHEL
- TensorFlow
- Ubuntu
Highlights
This is a remote position. The company is based in Canada and is building next-generation sovereign AI infrastructure. No specific application deadline or method is mentioned.
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