PMLEProfessional Machine Learning Engineer practice exams
Original questions written from the published objectives and cited to official documentation, never recalled exam content. How we verify, why not dumps.
What is ready now
- Exam code
- PMLE
- Cost
- $200USD
- Questions
- 50-60
- Duration
- 120minutes
- Passing score
- Not published by Google Cloud
- Format
- Multiple choice and multiple select
Fail and the retake is another $200. Practising until you are ready is the cheapest part of this.
What the exam tests
Exam domains and official weightings
From the official Google Cloud exam guides. Put your study time where the weight is.
The percentage is the exam weighting. The bar is our verified questions in that domain against the best covered one, so a short bar is where the bank is thin.
- Architecting low-code AI solutions13%16 verified
- Collaborating within and across teams to manage data and models16%19 verified
- Scaling prototypes into ML models21%25 verified
- Serving and scaling models20%24 verified
- Automating and orchestrating ML pipelines18%22 verified
- Monitoring AI solutions13%14 verified
Where to focus: The operational half is where people underprepare. Serving, pipelines and monitoring together are 51 percent of the exam, against 34 percent for building and scaling models. Google's own section weights sum to 101 rather than 100, so treat every figure as approximate.
Every ML Engineer objective, with practice questions mapped to each one
What the exam actually asks you to do
Multiple choice and multiple select, in Google's own words. No labs, no console access, and nothing to configure during the exam.
Item formats
- Multiple choice
- Multiple response
Nothing here needs a lab. Reading carefully and eliminating options is the whole skill. Google Cloud, Professional Machine Learning Engineer exam details ↗
ML Engineer practice exams
Full-length forms, 50 questions each, apportioned to the published domain weightings so every one stands alone as a representative sample. The questions in a numbered form are fixed, so two attempts on the same form are comparable.
Sit any of them under exam conditions, with the clock running and nothing revealed until you submit, or in study mode, with the full explanation after every answer. You choose when you start. 5 questions from across every form are free, with no account and no card.
Between sittings
The same bank the numbered forms are assembled from.
Open now
Quick Practice
All 120 verified questions, untimed, with the explanation after each answer.
Open now
Domain Drill
Every domain on its own, for the area a score report says is weakest.
Fills as you go
Review Missed
Re-asks the questions you got wrong. Nothing to review until you miss something.
Where ML Engineer fits
An honest study plan
1. Read the official objectives first
Download the official objectives from Google Cloud and skim every line. The exam can only test what’s listed there, it’s the contract.
2. Weight your study toward Scaling prototypes into ML models and Serving and scaling models
Together the top two domains are 41% of the exam. Practise them until your accuracy is consistently above 80%.
3. Drill weak domains, then sit a numbered practice exam
Use Domain Drill on your weakest areas, then sit a full-length form under exam conditions: 50 questions in 120 minutes, scored against the published pass mark. Book the real exam when you are consistently clearing that, not before.
Official free resources
Study from the source. These are Google Cloud’s own materials:
Official ML Engineer exam page & objectives ↗Keep reading
Free ML Engineer practice test
Ten real questions, playable now. No account, no card.
ML Engineer exam objectives
The full official blueprint, with practice pages on covered objectives.
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.
Frequently asked questions
How much of this is Vertex AI?
Most of it, under a new name. Google renamed Vertex AI to Gemini Enterprise Agent Platform during 2026, and the guide now uses that name throughout. The mechanisms are unchanged, so older study material describes the same exam.
Do I need to be able to write code?
Yes. The guide states the ML Engineer has strong programming skills and experience with distributed data processing tools. Scaling prototypes into ML models is the largest section at 21 percent and assumes you can read training code, not just describe it.
Is this an ML theory exam?
No. Roughly half the exam is operational: serving and scaling at 20 percent, pipelines at 18 and monitoring at 13. Knowing which serving pattern fits a latency requirement matters more than deriving an algorithm.
How long is it valid?
Two years, one less than the foundational and associate certifications. Renewal means passing the full exam again.
Ready to practice for PMLE?
Five questions from across every practice exam, plus 10 questions per certification in bank practice, with no account. Full explanations on every single one.