This skill covers tools, strategies, and principles for designing and managing AI workflows on HPC systems. It addresses orchestration, scheduling, automation, and reproducibility of AI pipelines across distributed infrastructure.

• External: Familiarity with AI training/inference steps and command-line environments
• Internal: None

• Define the components of a typical AI workflow (data preprocessing, training, evaluation, deployment).
• Describe the role of workflow engines (e.g., Snakemake, Nextflow, Airflow) in managing AI pipelines.
• Demonstrate how to schedule and monitor multi-stage AI tasks on HPC resources.
• Apply versioning and reproducibility best practices in AI workflow design.
• Understand error handling, checkpointing, and dependency resolution in distributed AI pipelines.

Caution: All text is AI generated