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Everything needed to plan for the GCP Professional ML Engineer (Professional ML Engineer) exam: number of questions, time limit, passing score, and the official domain weightings. For the study checklist itself, see the Professional ML Engineer study guide.
GCP Professional ML Engineer (Professional ML Engineer) is a Professional level Google Cloud certification exam with about 60 questions in 120 minutes. It covers 6 official domains: Architecting Low-Code ML Solutions (17%); Collaborating Within and Across Teams (17%); Scaling Prototypes Into ML Models (17%); Serving and Scaling Models (17%); Automating and Orchestrating ML Pipelines (16%); Monitoring ML Solutions (16%).
Exam code
Professional ML Engineer
Questions
~60
Time limit
120 min
Passing score
Competency-based
Official domains
6
Level
Professional
Provider
Google Cloud
Practice questions
300+ on CertStud
| Domain | Weight | What it covers |
|---|---|---|
| Architecting Low-Code ML Solutions | 17% | BigQuery ML, AutoML, pre-built APIs, RAG architectures |
| Collaborating Within and Across Teams | 17% | Data validation, responsible AI, model cards, ML metadata |
| Scaling Prototypes Into ML Models | 17% | Custom training, distributed training, hyperparameter tuning |
| Serving and Scaling Models | 17% | Vertex AI Endpoints, batch prediction, model optimization |
| Automating and Orchestrating ML Pipelines | 16% | Vertex AI Pipelines, Kubeflow, CI/CD for ML, Feature Store |
| Monitoring ML Solutions | 16% | Drift detection, model monitoring, retraining strategies |
Percentages reflect published official domain weightings. Prerequisite knowledge and current scoring rules are confirmed on the Google Cloud exam page before booking.
The Professional ML Engineer exam has approximately 60 questions. Question counts can vary slightly between deliveries, so treat 60 as the planning figure rather than a fixed number.
Candidates get about 120 minutes to complete the Professional ML Engineer exam, which works out to roughly 2 minute(s) per question at 60 questions.
The Professional ML Engineer exam is scored against a competency standard rather than a published percentage, so no single passing score applies. Confirm the current scoring standard on the official Google Cloud exam page before you book.
The Professional ML Engineer exam covers 6 official domains: Architecting Low-Code ML Solutions (17%), Collaborating Within and Across Teams (17%), Scaling Prototypes Into ML Models (17%), Serving and Scaling Models (17%), Automating and Orchestrating ML Pipelines (16%), Monitoring ML Solutions (16%).
Architecting Low-Code ML Solutions carries the heaviest weighting on the Professional ML Engineer exam at 17% of the exam. BigQuery ML, AutoML, pre-built APIs, RAG architectures
Professional ML Engineer is the exam code for GCP Professional ML Engineer (Google Cloud Professional Machine Learning Engineer), a Professional level Google Cloud certification exam covering 6 domains.
The Professional ML Engineer exam reports a competency-based result on a scaled score. Plan for roughly 60 questions across 120 minutes, weighted by domain: 17% Architecting Low-Code ML Solutions, 17% Collaborating Within and Across Teams, 17% Scaling Prototypes Into ML Models, 17% Serving and Scaling Models, 16% Automating and Orchestrating ML Pipelines, 16% Monitoring ML Solutions.
CertStud offers free Professional ML Engineer practice questions with detailed explanations, plus full-length practice exams and flashcards at https://certstud.com/certifications/google-cloud/professional-ml-engineer. Start with 10 free questions at https://certstud.com/try-free.