HPC Infrastructure and Support Engineer

3 weeks ago

london, United Kingdom asobbi Full time

About the Company A rapidly growing cloud provider is redefining high-performance computing with cutting-edge GPUaaS, delivering scalable, enterprise-grade AI infrastructure at unmatched efficiency. With deep ties to Nvidia, they’re quickly becoming a powerhouse in the US and Europe’s AI and ML ecosystem, providing solutions for HPC, AI, and deep learning workloads. Role Overview As the Principal HPC Support Engineer, you will play a pivotal role in maintaining and supporting high-performance computing environments on bare-metal infrastructure, primarily serving clients in research, higher education, and enterprise AI sectors. You will focus on both the software and networking aspects of HPC deployments, ensuring that large-scale GPU clusters remain operational, secure, and optimized for client needs. Key Responsibilities System Maintenance and Performance Optimization • Manage, maintain, and tune bare-metal HPC clusters running Linux-based operating systems (e.g., Fedora, Debian, Ubuntu). • Optimize Nvidia GPU compute environments, including CUDA, NCCL, and GPU resource management in multi-node HPC clusters. • Oversee high-speed networking configurations, including InfiniBand (Mellanox), RDMA, and Ethernet fabric tuning for low-latency HPC workloads. • Configure and fine-tune HPC schedulers (e.g., Slurm, OpenPBS, SGE) for optimal GPU workload distribution. • Implement containerization strategies (Podman, Docker) and orchestration platforms (K3s, Kubernetes) for managing distributed AI/ML workloads. Networking and Infrastructure Support • Configure, monitor, and troubleshoot high-performance network fabrics, ensuring low-latency, high-throughput communication between GPU nodes. • Deploy and maintain InfiniBand, RoCE, and high-speed Ethernet for HPC and AI clusters. • Collaborate with networking teams to optimize routing, switching, and load balancing for distributed computing environments. • Work closely with Nvidia engineers and system architects to implement GPUDirect Storage, NVLink, and Magnum IO for accelerated workloads. Security, Automation, and Monitoring • Maintain authentication and authorization systems such as Active Directory, OpenLDAP, and Keycloak. • Automate system provisioning and configuration using Ansible, Terraform, or other Infrastructure-as-Code tools. • Monitor system performance using Prometheus, Grafana, and ELK Stack, identifying and resolving bottlenecks in GPU workloads. • Implement security best practices for multi-tenant HPC clusters, ensuring compliance with industry standards. Troubleshooting and Client Support • Serve as the lead technical resource for diagnosing and resolving complex software, networking, and hardware issues in large-scale GPU clusters. • Analyze logs, conduct performance profiling, and debug CUDA, MPI, and RDMA-related issues. • Work closely with AI/ML research teams, cloud engineers, and enterprise clients to optimize workload performance. Collaboration and Process Improvement • Support the ongoing development of internal HPC test environments and customer POCs. • Work cross-functionally with Service Desk, Operations, and Service Delivery Management to ensure seamless service. • Provide technical documentation, training, and mentorship to junior team members.

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