Machine Learning Engineer Interview Questions in San Francisco, CA

Machine Learning Engineer Interview Questions in San Francisco, CA

Companies rely on machine learning engineers to help design and improve the systems that allow their software to improve on its own, rather than being specifically programmed. During the interview process, be prepared to be tested heavily on both computer science and data science knowledge with an emphasis on recognizing patterns and trends. A bachelor's degree in computer science or a related field will be required.

3,583 Machine Learning Engineer interview questions shared by candidates

Top Machine Learning Engineer Interview Questions & How to Answer

Here are three top machine learning engineer interview questions and how to answer them:

Question #1: What are the most important algorithms, programming terms, and theories to understand as a machine learning engineer?

How to answer: Be prepared to talk about things like Type I and Type II errors, supervised and unsupervised machine learning, ROC curves, and other key parts of machine learning. Employers want to know you have a strong knowledge of the technical aspects of the job position.

Question #2: How would you explain machine learning to someone who doesn't understand it?

How to answer: Sometimes machine learning engineers have to work with people who aren't familiar with the technical aspects of the job. Use this interview question as an opportunity to show your strong knowledge of the position and your communication abilities.

Question #3: How do you stay up to date with the latest news and trends in machine learning?

How to answer: By talking about how you're up to date with the latest news and trends in machine learning, you can show an employer that you're engaged in the industry, a skilled researcher, and self-motivated.

Top Interview Questions

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Machine Learning Engineer was asked...December 6, 2023

- Pytorch code explanation - ML end to end process - rec system design

Huawei Technologies

what are the activation function in CNN?


1. Backpropagation working 2. Gradient Clipping 3. Gradient Vanishing 4. Activation Function 5. Weight Utilization 6. Network Architect 7. LSTM 8. Transformers 9.Tokens 10.MobileNet SSD Arch


Leetcode questions except 1 question


NLP home assignment and describe my experience


What evaluation metric do you use if both False positive and False negative should be considered?

1 Answers



Will adversarial attack be useful in LLMs?


Machine learning questions about binary classification


The Coding problems were 1 LC easy and 2 LC medium problems.


They had me do the software engineer codesignal tech screen.

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