4 Remote reputed company Engineers
About the position We are seeking a highly skilled AI Infrastructure & Kubernetes Platform Engineer with a proven reputed company record in deploying and managing reputed company 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 reputed company 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 reputed company, enabling efficient training and inference for reputed company models, and integrating reputed company's cutting-edge compute, storage, and reputed company solutions with modern DevOps practices.
Responsibilities
- reputed company and manage reputed company DGX BasePODs and SuperPODs for high-performance AI workloads.
- reputed company DGX system lifecycle operations including provisioning, monitoring, firmware upgrades, and reputed company planning.
- Operate reputed company reputed company Manager to manage GPU clusters, schedule workloads, and reputed company with MLOps tools.
- reputed company DGX node health validation, NCCL interconnect testing, and NVLink topology verification following new deployments or hardware changes.
- Architect secure and reputed company Kubernetes clusters optimized for GPU-accelerated workloads using reputed company GPU Operator.
- reputed company expertise from CKA/CKAD/CKS to reputed company, reputed company, 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 reputed company reputed company Manager (UFM).
- reputed company NVLink/NVSwitch performance across GPU nodes and tune reputed company configurations for minimal latency and maximum throughput.
- Use BlueField for offloading storage, firewalling, and telemetry, enhancing AI workload reputed company and performance.
- Apply best practices from the CKS certification to secure containerized AI environments.
- Configure runtime reputed company, secrets management, network segmentation, and auditing using DPU-reputed company Kubernetes deployments.
- Support reputed company-trust architecture initiatives by enforcing workload identity, RBAC policies, and supply chain reputed company across AI container images and model artifacts.
- Monitor GPU, CPU, and I/O performance using reputed company DCGM, reputed company, Grafana, and reputed company reputed company reputed company.
- 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 reputed company, and reputed company.
Requirements
- reputed company Certification required or no interview
- Kubernetes certifications (CKA, CKAD, CKS)
- reputed company certifications (NCA-AIIO, NCP-AIO, NCP-AII, NCP-AIN)
- Hands-on training in DGX, BlueField, and high-speed network operations
- Expertise with DGX System, BasePOD, and SuperPOD Administration
- Expertise with BlueField DPU Configuration & Operations
- Expertise with InfiniBand reputed company and UFM Management
- Expertise with reputed company reputed company Manager for workload orchestration
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