Senior Infrastructure / HPC
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Key skills for this role
About the Role
VaporVM seeks a Senior HPC / Infrastructure Engineer to design, deploy, and operate enterprise-scale HPC and AI infrastructure. Requires 10+ years hands-on experience with NVIDIA AI ecosystem, Kubernetes, Slurm, and Linux.
Key Skills for This Role
Responsibilities
- Design, deploy, and operate large scale HPC and AI infrastructure environments from bare metal through workload orchestration
- Architect and manage NVIDIA GPU platforms including BCM, AI Enterprise, GPU Operator, and AI service enablement
- Configure, optimize, and maintain Slurm scheduling environments for high throughput and GPU intensive workloads
- Design and operate highly available Kubernetes clusters supporting AI/ML, analytics, and containerized workloads
- Enable and support NVIDIA NIM services and AI Blueprint deployments for enterprise AI initiatives
- Administer and optimize RHEL and Ubuntu environments ensuring stability, security, and performance
- Develop and maintain infrastructure automation frameworks and CI/CD pipelines
- Optimize performance across compute, GPU, storage, networking, and cluster resources
- Implement monitoring, observability, alerting, capacity planning, and operational best practices
- Enforce security, patch management, access controls, and compliance standards across the infrastructure stack
- Lead troubleshooting, root cause analysis, and resolution of complex infrastructure and platform issues
Requirements
- 10+ years hands on experience in HPC, Linux infrastructure, and enterprise platform engineering
- Active RHCE – Red Hat Certified Engineer
- Active CKA – Certified Kubernetes Administrator
- Proven track record building and operating production scale HPC, GPU, or AI infrastructure
- Deep expertise in Kubernetes, Slurm, Linux administration, and NVIDIA AI technologies
Full Job Posting
Position Overview
- We are seeking a highly experienced Senior HPC / Infrastructure Engineer with proven expertise in designing, deploying, and operating enterprise scale HPC and AI infrastructure environments.
- This role is ideal for a hands on technical leader who has built and managed production grade HPC platforms, GPU clusters, Kubernetes ecosystems, and AI infrastructure from the ground up.
- The successful candidate will play a critical role in architecting, optimizing, and maintaining mission critical compute environments that support advanced AI/ML, data science, and high performance workloads.
Required Certifications
- RHCE – Red Hat Certified Engineer (Active)
- CKA – Certified Kubernetes Administrator (Active)
Core Technical Expertise
- NVIDIA Base Command Manager (BCM)
- NVIDIA AI Enterprise
- NVIDIA GPU Operator & Network Operator
- NVIDIA NIM Inference Services
- NVIDIA AI Blueprints
- CUDA, GPU Drivers, and Performance Optimization
- Kubernetes (Architecture, Operations & Scaling)
- Slurm Workload Manager
- Distributed Computing Environments
- Red Hat Enterprise Linux (RHEL)
- Ubuntu LTS (Canonical)
- CI/CD Pipeline Design & Implementation
Key Responsibilities
- Design, deploy, and operate large scale HPC and AI infrastructure environments from bare metal through workload orchestration.
- Architect and manage NVIDIA GPU platforms, including BCM, AI Enterprise, GPU Operator, and AI service enablement.
- Configure, optimize, and maintain Slurm scheduling environments for high throughput and GPU intensive workloads.
- Design and operate highly available Kubernetes clusters supporting AI/ML, analytics, and containerized workloads.
- Enable and support NVIDIA NIM services and AI Blueprint deployments for enterprise AI initiatives.
- Administer and optimize RHEL and Ubuntu environments, ensuring stability, security, and performance.
- Develop and maintain infrastructure automation frameworks and CI/CD pipelines for platform and application deployment.
- Optimize performance across compute, GPU, storage, networking, and cluster resources.
- Implement monitoring, observability, alerting, capacity planning, and operational best practices.
- Enforce security, patch management, access controls, and compliance standards across the infrastructure stack.
- Lead troubleshooting, root cause analysis, and resolution of complex infrastructure and platform issues.
Candidate Profile
- 10+ years of hands on experience in HPC, Linux infrastructure, and enterprise platform engineering.
- Proven track record of building and operating production scale HPC, GPU, or AI infrastructure environments.
- Deep expertise in Kubernetes, Slurm, Linux administration, and NVIDIA AI technologies.
- Strong understanding of distributed systems, workload scheduling, cluster management, and performance optimization.
- Experience supporting AI/ML, data science, and high performance computing workloads at scale.
- Strong analytical, troubleshooting, and problem solving skills.
- Ability to work across infrastructure, platform, automation, and AI enablement domains.
- Demonstrated ownership mindset with a history of delivering reliable, scalable, and high performing solutions.
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