Senior Infrastructure Engineer (HPC)
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Key skills for this role
About the Role
We are seeking a Senior Infrastructure Engineer to deploy, configure, and manage large-scale High-Performance Computing (HPC) environments. The role requires expertise in Linux administration, NVIDIA GPU infrastructure, Slurm, Kubernetes, and CI/CD automation.
Key Skills for This Role
Responsibilities
- Design, implement, and maintain end to end HPC clusters including compute nodes, storage layers, high speed networking, and management infrastructure
- Provision and administer NVIDIA Base Command Manager (BCM) for bare metal cluster deployment and GPU fleet monitoring
- Deploy, maintain, and integrate the NVIDIA AI Enterprise Suite with MLOps frameworks
- Manage NVIDIA GPU Operator and Network Operator within Kubernetes environments
- Configure and support NVIDIA NIM inference services and implement NVIDIA Blueprint reference architectures
- Install, administer, and optimize Slurm environments including partitions, QoS policies, and fair share scheduling
- Build and manage Kubernetes clusters using kubeadm including high availability control planes
- Administer and maintain Red Hat Enterprise Linux (RHEL) and Canonical Ubuntu systems across all cluster nodes
- Develop and maintain CI/CD pipelines using GitLab CI and GitHub Actions
- Analyze and optimize GPU and CPU performance, troubleshooting bottlenecks
- Implement monitoring and observability solutions using Prometheus, Grafana, and DCGM
- Ensure adherence to security best practices through system hardening, kernel patching, RBAC implementation, and compliance monitoring
Requirements
- Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or related field
- Minimum of 10 years of hands on experience in High Performance Computing (HPC) and infrastructure engineering
- Active Red Hat Certified Engineer (RHCE) certification
- Active Certified Kubernetes Administrator (CKA) certification
- Proven experience designing, deploying, and managing large scale HPC environments
- Strong hands on expertise with NVIDIA Base Command Manager (BCM) and NVIDIA AI Enterprise ecosystem
- Experience with NVIDIA GPU Operator, Network Operator, NVIDIA NIMs, and NVIDIA Blueprints
- Extensive experience administering Slurm and managing workload scheduling in HPC environments
- Strong knowledge of Kubernetes cluster deployment and administration
- Solid experience with Red Hat Enterprise Linux (RHEL) and Canonical Ubuntu LTS administration
- Proficiency in CUDA, GPU drivers, and GPU infrastructure management
- Experience building and maintaining CI/CD pipelines using GitLab CI and/or GitHub Actions
Full Job Posting
Job Summary
- Deploying, configuring, and managing large scale High Performance Computing (HPC) environments.
- Demonstrating practical expertise across Linux administration (RHEL and Ubuntu), NVIDIA GPU infrastructure, Slurm workload scheduling, Kubernetes, CI/CD automation, and the NVIDIA Enterprise software ecosystem.
Key Responsibilities
- Design, implement, and maintain end to end HPC clusters, including compute nodes, storage layers, high speed networking (InfiniBand/RoCE), and management infrastructure.
- Provision and administer NVIDIA Base Command Manager (BCM) for bare metal cluster deployment, operating system lifecycle management, and GPU fleet monitoring.
- Deploy, maintain, and integrate the NVIDIA AI Enterprise Suite with MLOps frameworks, including NeMo, Triton, and RAPIDS.
- Manage NVIDIA GPU Operator and Network Operator within Kubernetes environments to automate GPU driver and CUDA lifecycle management, DCGM exporter, and MIG configuration.
- Configure and support NVIDIA NIM inference services and implement NVIDIA Blueprint reference architectures for production AI workloads.
- Install, administer, and optimize Slurm environments, including partitions, QoS policies, fair share scheduling, node accounting, MPI integration, and hybrid Slurm on Kubernetes scheduling.
- Build and manage Kubernetes clusters using kubeadm, including high availability control planes, etcd backup strategies, and zero downtime upgrades.
- Administer and maintain Red Hat Enterprise Linux (RHEL) and Canonical Ubuntu systems across all cluster nodes.
- Develop and maintain CI/CD pipelines using GitLab CI and GitHub Actions to automate infrastructure provisioning and software delivery.
- Analyze and optimize GPU and CPU performance, troubleshooting bottlenecks across hardware, drivers, MPI fabric, and application layers.
- Implement monitoring and observability solutions using Prometheus, Grafana, and DCGM, and establish alerting and capacity planning mechanisms.
- Ensure adherence to security best practices through system hardening, kernel patching, RBAC implementation, and compliance monitoring across the HPC environment.
Requirements
- Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or a related field.
- Minimum of 10 years of hands on experience in High Performance Computing (HPC) and infrastructure engineering.
- Active Red Hat Certified Engineer (RHCE) certification.
- Active Certified Kubernetes Administrator (CKA) certification.
- Proven experience designing, deploying, and managing large scale HPC environments.
- Strong hands on expertise with NVIDIA Base Command Manager (BCM) and the NVIDIA AI Enterprise ecosystem.
- Experience with NVIDIA GPU Operator, Network Operator, NVIDIA NIMs, and NVIDIA Blueprints.
- Extensive experience administering Slurm and managing workload scheduling in HPC environments.
- Strong knowledge of Kubernetes cluster deployment and administration, including high availability and lifecycle management.
- Solid experience with Red Hat Enterprise Linux (RHEL) and Canonical Ubuntu LTS administration.
- Proficiency in CUDA, GPU drivers, and GPU infrastructure management.
- Experience building and maintaining CI/CD pipelines using GitLab CI and/or GitHub Actions.
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