Professional Machine Learning Engineer

Build, deploy, and monitor production ML and generative AI solutions on Gemini Enterprise Agent Platform, and track your readiness for the Professional Machine Learning Engineer exam.

Expert

Prepare and test your skills

Expert

Prepare and test your skills

Google Cloud feature

BigQuery ML model monitoring

Topic in 1 exam domain

X LinkedIn Facebook Reddit

A set of tools and functionalities in BigQuery to track and evaluate ML model performance, data skew, and data drift over time.

Where this appears on the exam

1 subdomain in 1 of 6 domains

Domain 3
Scaling prototypes into ML models
~21% of exam
1. 3.1Building models given the task considering cost, complexity, latency, and scalability
  - Choosing the product (e.g., Agent Platform AutoML, BigQuery ML, and Agent Platform Pipelines)

How learners score on this topic

Last updated October 25, 2026

Professional Machine Learning Engineer

Build, deploy, and monitor production ML and generative AI solutions on Gemini Enterprise Agent Platform, and track your readiness for the Professional Machine Learning Engineer exam.

Expert

Prepare and test your skills

Expert

Prepare and test your skills

Google Cloud feature

BigQuery ML model monitoring

Topic in 1 exam domain

X LinkedIn Facebook Reddit

A set of tools and functionalities in BigQuery to track and evaluate ML model performance, data skew, and data drift over time.

Where this appears on the exam

1 subdomain in 1 of 6 domains

Domain 3
Scaling prototypes into ML models
~21% of exam
1. 3.1Building models given the task considering cost, complexity, latency, and scalability
  - Choosing the product (e.g., Agent Platform AutoML, BigQuery ML, and Agent Platform Pipelines)

How learners score on this topic

Last updated October 25, 2026