An ML engineer needs to run intensive model training jobs each month that can take...

Amazon EC2 Spot Instances provide unused compute capacity at discounts of up to 90%. AWS documentation strongly recommends Spot Instances for interruptible workloads such as long-running ML training jobs that can resume from checkpoints.

By enabling automatic checkpointing, SageMaker saves model state periodically to Amazon S3. If the Spot Instance is interrupted, training can resume with minimal loss of progress.

Reserved Instances and Savings Plans require long-term commitment and are not as cost-effective for sporadic workloads. On-Demand Instances are the most expensive option.

Therefore, Option D is the most cost-effective solution.