Exam Professional Machine Learning Engineer topic 1 question 329 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 329
Topic #: 1

[All Professional Machine Learning Engineer Questions]

You deployed a conversational application that uses a large language model (LLM). The application has 1,000 users. You collect user feedback about the verbosity and accuracy of the model 's responses. The user feedback indicates that the responses are factually correct but users want different levels of verbosity depending on the type of question. You want the model to return responses that are more consistent with users' expectations, and you want to use a scalable solution. What should you do?

A. Implement a keyword-based routing layer. If the user's input contains the words "detailed" or "description," return a verbose response. If the user's input contains the word "fact." re-prompt the language model to summarize the response and return a concise response.
B. Ask users to provide examples of responses with the appropriate verbosity as a list of question and answer pairs. Use this dataset to perform supervised fine tuning of the foundational model. Re-evaluate the verbosity of responses with the tuned model.
C. Ask users to indicate all scenarios where they expect concise responses versus verbose responses. Modify the application 's prompt to include these scenarios and their respective verbosity levels. Re-evaluate the verbosity of responses with updated prompts.
D. Experiment with other proprietary and open-source LLMs. Perform A/B testing by setting each model as your application's default model. Choose a model based on the results.

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Suggested Answer: C 🗳️

by Duke_CT at June 20, 2025, 3:52 a.m.

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Duke_CT

1 month, 4 weeks ago

Selected Answer: C

Hmm, seems like A from what I studied.

upvoted 1 times

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