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IT Search Corp

This is a remote position.

NVIDIA AI Infrastructure & Kubernetes Platform Engineer Remote

Artificial IntelligenceArtificial IntelligenceFull TimeRemoteMid LevelTeam 2-10

Location

United States

Posted

70 days ago

Salary

$90 - $130 / hour

Seniority

Mid Level

No structured requirement data.

Job Description

NVIDIA AI Infrastructure & Kubernetes Platform Engineer Remote

IT Search Corp

NVIDIA AI Infrastructure & Kubernetes Platform Engineer NVIDIA AI Infrastructure & Kubernetes Platform Engineer (DGX Systems) Alternate titles depending on context: - AI Platform Architect – DGX & SuperPOD - AI Infrastructure DevOps Engineer – NVIDIA DGX Stack - Senior AI Systems Engineer – DGX | Kubernetes | InfiniBand Job Description: We are seeking a highly skilled AI Infrastructure & Kubernetes Platform Engineer with a proven track record in deploying and managing NVIDIA DGX-based AI clusters, orchestrating containerized AI workloads using Kubernetes, and ensuring secure, high-throughput operations across InfiniBand-powered networks. The ideal candidate will hold a combination of Kubernetes certifications (CKA, CKAD, CKS) and NVIDIA certifications (NCA-AIIO, NCP-AIO, NCP-AII, NCP-AIN), coupled with hands-on training in DGX, BlueField, and high-speed network operations. This position plays a key role in supporting AI/ML infrastructure at scale, enabling efficient training and inference for complex models, and integrating NVIDIA's cutting-edge compute, storage, and fabric solutions with modern DevOps practices. Core Responsibilities: AI Infrastructure Operations - Deploy and manage NVIDIA DGX BasePODs and SuperPODs for high-performance AI workloads. - Oversee DGX system lifecycle operations including provisioning, monitoring, firmware upgrades, and capacity planning. - Operate Base Command Manager to manage GPU clusters, schedule workloads, and integrate with MLOps tools. - Perform DGX node health validation, NCCL interconnect testing, and NVLink topology verification following new deployments or hardware changes. Kubernetes Platform Engineering - Architect secure and scalable Kubernetes clusters optimized for GPU-accelerated workloads using NVIDIA GPU Operator. - Leverage expertise from CKA/CKAD/CKS to develop, deploy, and secure AI applications on Kubernetes. - Implement CI/CD pipelines and GitOps methodologies for deploying and managing ML workflows. High-Performance Networking & DPUs - Administer InfiniBand networks and BlueField DPUs using Unified Fabric Manager (UFM). - Enable NVLink/NVSwitch performance across GPU nodes and tune fabric configurations for minimal latency and maximum throughput. - Use BlueField for offloading storage, firewalling, and telemetry, enhancing AI workload security and performance. Security & Compliance - Apply best practices from the CKS certification to secure containerized AI environments. - Configure runtime security, secrets management, network segmentation, and auditing using DPU-enhanced Kubernetes deployments. - Support zero-trust architecture initiatives by enforcing workload identity, RBAC policies, and supply chain integrity across AI container images and model artifacts. Monitoring, Telemetry & Optimization - Monitor GPU, CPU, and I/O performance using NVIDIA DCGM, Prometheus, Grafana, and Base Command APIs. - Tune system performance and model training pipelines for cost-efficiency and throughput. - Build and maintain operational runbooks, incident response playbooks, and SLA reporting dashboards covering GPU utilization, thermal thresholds, and fabric health. Qualifications: Certifications a plus: - Certified Kubernetes Administrator (CKA) - Certified Kubernetes Application Developer (CKAD) - Certified Kubernetes Security Specialist (CKS) - NVIDIA Certified Associate: AI Infrastructure & Operations (NCA-AIIO) - NVIDIA Certified Professional: AI Infrastructure (NCP-AII) - NVIDIA Certified Professional: AI Operations (NCP-AIO) - NVIDIA Certified Professional: AI Networking (NCP-AIN) Expertise With: - DGX System, BasePOD, and SuperPOD Administration - BlueField DPU Configuration & Operations - InfiniBand Fabric and UFM Management - Base Command Manager for workload orchestration Technical Skills: - Kubernetes, Helm, GPU Operator, Kubeflow - DevOps tools: Ansible, Terraform, GitOps, CI/CD pipelines - Storage: NFS, BeeGFS, Lustre - Networking: RoCE, InfiniBand, DPU offload, gRPC, RDMA - Programming/scripting: Python, YAML, Bash This is a remote position.

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