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Machine Learning Interview Questions

"To get a job in machine learning, you must have the programming and mathematical knowledge to create artificial intelligence that is capable of learning new tasks without being explicitly coded. In an interview you may be asked about your experience with pertinent coding languages such as Java and C++ as well as with writing algorithms. The interview will be comprised mainly of technical questions that test your knowledge of the fundamental concepts of machine learning such as data mining and signal processing."

8,197 machine learning interview questions shared by candidates

In technical interview: They wanted to know mostly about the solution I presented for the take home assessment. In product and engineering interview: They asked questions about my past experience, specifically the products I build
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Senior Machine Learning Scientist

Interviewed at Acuity Insights

3.8★
Mar 4, 2025

In technical interview: They wanted to know mostly about the solution I presented for the take home assessment. In product and engineering interview: They asked questions about my past experience, specifically the products I build

1st round: 4 leet-code style questions on CodeSignal. 2 easy, 2 medium/hard. 2nd round: 4 interviews in total a. ML job fit interview: was asked about some ML basics such as bias/variance tradeoff, how to deploy models, reduce latency during inference b. ML job fit interview: One coding question (find number of primes until N), and some questions about ML model deployment. c. Case Study: simple quantitative analysis of cost-benefit analysis about simple vs rigorous testing of software release cycles. d. Behavioral: 3 questions about past experience - describe a challenging situation you encountered - describe a time when you had to prioritize one task over another - describe when you changed status quo
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Lead Machine Learning Engineer

Interviewed at Capital One

3.6★
Jul 10, 2022

1st round: 4 leet-code style questions on CodeSignal. 2 easy, 2 medium/hard. 2nd round: 4 interviews in total a. ML job fit interview: was asked about some ML basics such as bias/variance tradeoff, how to deploy models, reduce latency during inference b. ML job fit interview: One coding question (find number of primes until N), and some questions about ML model deployment. c. Case Study: simple quantitative analysis of cost-benefit analysis about simple vs rigorous testing of software release cycles. d. Behavioral: 3 questions about past experience - describe a challenging situation you encountered - describe a time when you had to prioritize one task over another - describe when you changed status quo

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