Exam objectives
PMLEProfessional Machine Learning Engineer exam objectives
The published blueprint is the contract: the exam can only test what is on this list. Domains carry their official weightings, and objectives with a practice page link straight to questions written for that objective.
Titles and weightings from the official objectives. Google Cloud exam page ↗
Architecting low-code AI solutions
13%of examCollaborating within and across teams to manage data and models
16%of examScaling prototypes into ML models
21%of examServing and scaling models
20%of examAutomating and orchestrating ML pipelines
18%of examMonitoring AI solutions
13%of examObjectives marked Practice open a page of original questions written for that objective, each with a full explanation cited to Google Cloud documentation.
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ML Engineer practice questions
Free sample questions with the full explanation on every answer.
Free ML Engineer practice test
Ten real questions, playable now. No account, no card.
ML Engineer passing score
The exact cut score, what kind of number it is, and the retake terms.
How hard is ML Engineer?
An honest difficulty read from the format, the clock and the weights.