NVIDIA AI Infrastructure & Kubernetes Platform Engineer (DGX Systems)

One IT

Location: US
Workplace: Remote
Employment: Contract
Salary: USD 90–100/hr

Posted 28d ago

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Responsibilities

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
Architect secure, scalable Kubernetes clusters optimized for GPU-accelerated workloads using the NVIDIA GPU Operator
Apply CKA/CKAD/CKS expertise to develop, deploy, and secure AI applications on Kubernetes
Implement CI/CD pipelines and GitOps methodologies for deploying and managing ML workflows
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 to offload storage, firewalling, and telemetry, strengthening AI workload security and performance
Apply CKS best practices to secure containerized AI environments
Configure runtime security, secrets management, network segmentation, and auditing across DPU-enhanced Kubernetes deployments
Support zero-trust initiatives by enforcing workload identity, RBAC policies, and supply-chain integrity across AI container images and model artifacts
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 dashboards covering GPU utilization, thermal thresholds, and fabric health

Requirements

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)
DGX System, BasePOD, and SuperPOD administration
BlueField DPU configuration and operations
InfiniBand fabric and UFM management
Base Command Manager for workload orchestration
Kubernetes, Helm, and the NVIDIA GPU Operator
DevOps tooling: Ansible, Terraform, GitOps, CI/CD pipelines
Programming/scripting: Python, YAML, Bash
Bachelor's degree in Computer Science, Engineering, or related field or equivalent hands-on experience

Preferred

Kubeflow and broader MLOps pipeline experience
Parallel/HPC storage: NFS, BeeGFS, Lustre
Advanced networking: RoCE, RDMA, gRPC, and DPU offload tuning

Skills

NVIDIA DGX
Kubernetes
NVIDIA GPU Operator
InfiniBand
BlueField DPU
Unified Fabric Manager
Base Command Manager
NVLink
NVSwitch
Helm
Ansible
Terraform
GitOps
CI/CD
Python
YAML
Bash
NVIDIA DCGM
Prometheus
Grafana
Kubeflow
NFS
BeeGFS
Lustre
RoCE
RDMA
gRPC

Responsibilities

Requirements

Preferred

Skills

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