Strong expertise in Kubernetes administration, including custom resource definitions, operators
Hands-on experience with Slurm workload management, including job scheduling, resource allocation
Experience with deploying and managing distributed training systems at scale
Deep understanding of container orchestration and distributed systems architecture
High level familiarity with LLM architecture and training processes (Multi-Head Attention
Experience managing GPU clusters and optimizing compute resource utilization

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