Google Professional Machine Learning Engineer Questions and Answers
200 questions organized by topic with detailed explanations
Google
GCP-PMLE
200 questions
6 topics
Updated May 2026Architecting low-code AI solutions
27 questions9 easy13 medium5 hard~13% of exam
A team wants a single Vertex AI location to discover, test, customize, and deploy models from Google and partners. Which...In Model Garden, which model category contains pretrained multitask large models that can be tuned or customized for spe...A company has already built an agent with ADK and now needs a managed runtime that can deploy, manage, and scale that ag...
Collaborating within and across teams to manage data and models
26 questions8 easy13 medium5 hard~14% of exam
Which statement about Vertex AI managed datasets is correct?Data stewards need to search for Vertex AI datasets and models across projects and regions from one metadata layer. Whic...A platform team wants a central repository where they can version models, assign aliases, and deploy a chosen version to...
Scaling prototypes into ML models
36 questions8 easy18 medium10 hard~18% of exam
A team configures a serverless training job to use TPU VMs and wants to scale a single worker pool to many replicas. Whi...A distributed multi-node GPU training job is spending too much time in all-reduce communication. Which Vertex AI optimiz...A team has a non-Python training application with private dependencies and a framework version that is not covered by Ve...
Serving and scaling models
40 questions8 easy21 medium11 hard~20% of exam
A company built a model in BigQuery ML and wants to manage it through Vertex AI without exporting the model artifacts fi...A custom model must support online predictions with low latency. Which architectural condition must be satisfied before ...After an AutoML model finishes training, what happens with respect to Model Registry?
Automating and orchestrating ML pipelines
44 questions11 easy23 medium10 hard~22% of exam
Monitoring AI solutions
27 questions8 easy12 medium7 hard~13% of exam
A deployed model has access to its original training data, and the team wants to detect whether production feature distr...In Vertex AI Model Monitoring v1, which distance metrics are used by default to compare feature distributions for catego...Which statement correctly distinguishes Vertex AI Model Monitoring v1 from v2?
All Questions
| # | Question | Topic | Difficulty |
|---|---|---|---|
| 1 | A team configures a serverless training job to use TPU VMs and wants to scale a single worker pool t... | Scaling prototypes into ML models | hard |
| 2 | A team wants a single Vertex AI location to discover, test, customize, and deploy models from Google... | Architecting low-code AI solutions | easy |
| 3 | A company built a model in BigQuery ML and wants to manage it through Vertex AI without exporting th... | Serving and scaling models | hard |
| 4 | A custom model must support online predictions with low latency. Which architectural condition must ... | Serving and scaling models | hard |
| 5 | After an AutoML model finishes training, what happens with respect to Model Registry? | Serving and scaling models | medium |
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