Machine Learning Engineer Interview Questions

6,179 machine learning engineer interview questions shared by candidates

For the take home exercise, they send you a problem where you have to build a model to solve it. For the interview they ask you specific deep learning questions as well as plotting and analyzing probability distributions.
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Machine Learning Engineer

Interviewed at Scale

3.6
Jan 13, 2021

For the take home exercise, they send you a problem where you have to build a model to solve it. For the interview they ask you specific deep learning questions as well as plotting and analyzing probability distributions.

Questions about academic/professional path, salary expectations, etc. "Explain the bias variance trade-off" "What's the difference between L1 and L2 regularisation" "Explain gradient decent (GD). Why do we use Stochastic gradient decent (SGD) instead of GD. Mention some other variants of optimisers." "Describe a ML system. What are the different components that go into it?" "Suppose you are asked to deploy a model as a micro-service. What are the various components you need to think about when designing the service. Give a generic explanation for each component and one particular instantiation using one or more technology." "What are Directed Acyclic Graphs (DAG)?" "What should be a leader?" "What are your strengths and your weaknesses?" "What motivates you to wake up everyday?"
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Machine Learning Engineer

Interviewed at Teya

3.4
Aug 16, 2022

Questions about academic/professional path, salary expectations, etc. "Explain the bias variance trade-off" "What's the difference between L1 and L2 regularisation" "Explain gradient decent (GD). Why do we use Stochastic gradient decent (SGD) instead of GD. Mention some other variants of optimisers." "Describe a ML system. What are the different components that go into it?" "Suppose you are asked to deploy a model as a micro-service. What are the various components you need to think about when designing the service. Give a generic explanation for each component and one particular instantiation using one or more technology." "What are Directed Acyclic Graphs (DAG)?" "What should be a leader?" "What are your strengths and your weaknesses?" "What motivates you to wake up everyday?"

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