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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #36

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #36: Real Exam Question with Answer & Explanation

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Submitted by omar99· Apr 18, 2026ML pipeline operationalization

Question

You manage a team of data scientists who use a cloud-based backend system to submit training jobs. This system has become very difficult to administer, and you want to use a managed service instead. The data scientists you work with use many different frameworks, including Keras, PyTorch, theano, Scikit-learn, and custom libraries. What should you do?

Options

  • AUse the AI Platform custom containers feature to receive training jobs using any framework.
  • BConfigure Kubeflow to run on Google Kubernetes Engine and receive training jobs through TF
  • CCreate a library of VM images on Compute Engine, and publish these images on a centralized
  • DSet up Slurm workload manager to receive jobs that can be scheduled to run on your cloud

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Topics

#ML training#Managed services#Custom containers#Multi-framework support
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