
AI Infrastructure Specialist
5 days ago
Job Title: AI Infrastructure Engineer
Description:
We are seeking a highly skilled engineer to design and build platforms for AI workloads in enterprise environments.
- Kubernetes Expertise:
- A deep understanding of container orchestration platforms, particularly Red Hat OpenShift and CNCF Kubernetes.
- Proficiency in deploying and supporting GPU-accelerated workloads and tools like NVIDIA GPU Operator and DCGM.
- The ability to integrate Kubernetes with AI/ML workloads and GPU infrastructure in hybrid or private cloud environments.
- HPC Experience:
- Hands-on experience architecting HPC clusters, including GPU/compute nodes and HPC storage technologies.
- Familiarity with high-speed networking (e.g., InfiniBand, Mellanox, RoCE).
- Experience with HPC cluster management tools such as HPE Cluster Management or NVIDIA Base Command Manager.
- Infrastructure & Hardware Stack:
- A strong foundation in Linux system administration (RHEL / SLES /Ubuntu) and virtualization.
- A primary focus on HPE servers and storage; experience with Dell, Lenovo, Supermicro, NVIDIA DGX/HGX platforms is also acceptable.
- AI Platform Enablement:
- Experience deploying and supporting NVIDIA AI Enterprise and related AI/ML frameworks.
- Familiarity with DevOps/MLOps practices, including CI/CD, Infrastructure as Code, and cloud-native security.
Requirements:
- Demonstrated success in delivering infrastructure projects, including platform build-outs for AI/ML and HPC workloads.
- The ability to collaborate effectively with cross-functional teams and align technical solutions with business objectives.
- Candidates with strong Kubernetes or HPC and AI/ML experience but limited infrastructure hardware exposure may be considered if they demonstrate trainability in server and platform environments.
Scope of Work:
This is a delivery-focused role with limited presales involvement. The engineer will be responsible for designing and building platforms to support enterprise-grade AI workloads.
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