Top Interview Questions for Machine Learning Engineer
A Machine Learning(ML) Engineer is someone who focuses on researching, building, and designing self-running artificial intelligence (AI) systems to automated models.
According to recent surveys, the spending on AI systems will reach 97.9$ billion by 2023.
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Hard Skills
Use these questions to identify a candidate’s technical knowledge and abilities
Soft Skills
Use these questions to assess a candidate’s personality traits and cognitive skills
What to look for while interviewing for a Machine Learning Engineer?
The skills required for the Machine Learning Engineer position are Python, Java programming, and Natural Language Processing, etc. Therefore, look for a candidate who has knowledge of all these.
Here are some skills to look out for when hirirng a Machine Learning Engineer
Role-specific skills to look for: Mathematical skills, Data analysis, Python, Java programming, and Natural Language Processing
Soft skills to look for: Problem Solving, Analytical, reasoning ability, communication skills, and Team management.
Pro Tip: Always screen before you interview. Use Online Assessment to screen applicants for ML engineer positions before blocking your time for an in-person interview.
Questions to ask while interviewing a Machine Learning Engineer
We have compiled a set of questions with the help of 70+ hiring managers at different organizations.
Top Role-based interview questions for Machine Learning Engineer
You are given a data set. Let’s suppose when you build a classification model you achieved an accuracy of 90%. What can you do about this?
Purpose of this interview question:
This question is designed to test the analytical skills and problem-solving abilities of the candidate.
What to listen for:
- The top candidates would list out the ways of improving the data accuracy.
Can you explain false negative, false positive, true negative, and true positive with a simple example?
Purpose of this interview question:
The following question is designed to test the knowledge of the candidate about the basics of Machine learning.
What to listen for:
- Make sure the example candidate provides explains all the terms false negative, false positive, true negative, and true positive.
What do you know about Kernel SVM?
Purpose of this interview question:
Knowledge of basic machine learning concepts like Kernel SVM is a sign of a top candidate, as it is one of the best-known algorithms of Machine learning.
What to listen for:
- Listen for the specific terms that explain Kernel SVM.
How to screen Machine Learning Engineer for soft skills
How do you stay up to date with the latest technologies?
Purpose of this interview question:
Being updated with the latest trends in the market is a sign of a top candidate.
What to listen for:
- Look for evidence of the understanding of the new trends in the candidate.
What strengths do you think are most important for your job position?
Purpose of this interview question:
Being aware of the responsibility and skills required as a professional is a sign of a top candidate.
What to listen for:
- Listen for the specific skills required for a ML engineer and if the candidate fits the company culture or not.
What influenced you in this career?
Purpose of this interview question:
With this question, you can test the candidate’s dedication, influence, and self-awareness.
What to listen for:
- Listen for the sign of dedication or other skills with which the candidate has achieved the required skills to get a job role of ML engineer.
Start Optimizing your Machine Learning Engineer Hiring today
Find and hire talent with confidence. If your candidate doesn’t know the answer to the above questions and you’re hiring for a ML Engineer position, then they’re probably not a great fit.
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