Free Google Professional-Machine-Learning-Engineer Exam Questions

Become Google Certified with updated Professional-Machine-Learning-Engineer exam questions and correct answers

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Total 289 Questions | Updated On: Feb 09, 2026

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Question 1

You are developing ML models with Al Platform for image segmentation on CT scans. You frequently update your model architectures based on the newest available research papers, and have to rerun training on the same dataset to benchmark their performance. You want to minimize computation costs and manual intervention while having version control for your code. What should you do?

A : Use Cloud Functions to identify changes to your code in Cloud Storage and trigger a retraining job

B : Use the gcloud command-line tool to submit training jobs on Al Platform when you update your code

C : Use Cloud Build linked with Cloud Source Repositories to trigger retraining when new code is pushed to the repository

D : Create an automated workflow in Cloud Composer that runs daily and looks for changes in code in Cloud Storage using a sensor.

Answer: C

Question 2

You are training an object detection machine learning model on a dataset that consists of three million X-ray images, each roughly 2 GB in size. You are using Vertex AI Training to run a custom training application on a Compute Engine instance with 32-cores, 128 GB of RAM, and 1 NVIDIA P100 GPU. You notice that model training is taking a very long time. You want to decrease training time without sacrificing model performance. What should you do?

A : crease the instance memory to 512 GB and increase the batch size.

B : place the NVIDIA P100 GPU with a v3-32 TPU in the training job.

C : able early stopping in your Vertex AI Training job

D : able early stopping in your Vertex AI Training job

Answer: C

Question 3

You recently deployed an ML model. Three months after deployment, you notice that your model is underperforming on certain subgroups, thus potentially leading to biased results. You suspect that the inequitable performance is due to class imbalances in the training data, but you cannot collect more data. What should you do? (Choose two.)

A : move training examples of high-performing subgroups, and retrain the model.

B : an additional objective to penalize the model more for errors made on the minority class, and retrain the model

C : move the features that have the highest correlations with the majority class.

D : ample or reweight your existing training data, and retrain the model

E : deploy the model, and provide a label explaining the model's behavior to users.

Answer: B,D

Question 4

You work for a bank You have been asked to develop an ML model that will support loan application decisions. You need to determine which Vertex Al services to include in the workflow You want to track the model's training parameters and the metrics per training epoch. You plan to compare the performance of each version of the model to determine the best model based on your chosen metrics. Which Vertex Al services should you use?

A : Vertex ML Metadata Vertex Al Feature Store, and Vertex Al Vizier

B : Vertex Al Pipelines. Vertex Al Experiments, and Vertex Al Vizier

C : Vertex ML Metadata Vertex Al Experiments, and Vertex Al TensorBoard

D : Vertex Al Pipelines. Vertex Al Feature Store, and Vertex Al TensorBoard

Answer: D

Question 5

You work for a semiconductor manufacturing company. You need to create a real-time application that automates the quality control process High-definition images of each semiconductor are taken at the end of the assembly line in real time. The photos are uploaded to a Cloud Storage bucket along with tabular data that includes each semiconductor's batch number serial number dimensions, and weight You need to configure model training and serving while maximizing model accuracy. What should you do?

A : Use Vertex Al Data Labeling Service to label the images and train an AutoML image classification model. Deploy the model and configure Pub/Sub to publish a message when an image is categorized into the failing class.

B : Use Vertex Al Data Labeling Service to label the images and train an AutoML image classification model. Schedule a daily batch prediction job that publishes a Pub/Sub message when the job completes.

C : Convert the images into an embedding representation Import this data into BigQuery, and train a BigQuery. ML K-means clustenng model with two clusters Deploy the model and configure Pub/Sub to publish a message when a semiconductor's data is categorized into the failing cluster.

D : Import the tabular data into BigQuery use Vertex Al Data Labeling Service to label the data and train an AutoML tabular classification model Deploy the model and configure Pub/Sub to publish a message when a semiconductor's data is categorized into the failing class.

Answer: D

Page: 1 / 58

Total 289 Questions | Updated On: Feb 09, 2026

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