Leads customer implementations of LLM and generative-AI systems from architecture through production, building full-stack solutions and improving model quality.
About this role
This role sits in the AI and HPC infrastructure organization, which designs and builds large-scale AI data centers and computing platforms. The engineer helps turn GPU infrastructure into an external cloud service, covering compute, storage, architecture, construction, and quality improvement for a GPU cloud platform.
The work spans GPU cluster architecture, GPU servers, Kubernetes, GPU management systems, NVIDIA software such as drivers and CUDA, high-speed file systems, object storage, performance evaluation, and provisioning automation. The engineer also examines and selects technologies, analyzes technical issues, coordinates vendors, and leads construction and operational design across the platform.
Applicants must have practical experience building servers, storage, or virtualization platforms such as OpenStack or Kubernetes, plus experience collaborating with internal and external stakeholders, including vendors. Depending on the role track, the posting requires practical design and construction experience in server or storage environments, or broader IT infrastructure experience; the management track also requires people-management experience.
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