Machine Learning Engineer Interview Questions

Table of Contents

    Depending on your company, the meaning of a machine learning engineer for you might be a data scientist, data engineer, AI engineer, or others. With the future being in the hands of technology, this is a crucial role and requires the assessment of candidates in various arenas. Ensure you ask questions based on algorithms and ML theory, programming skills, interest in machine learning, and the industry or product-related topics. 

    Here are a few questions that will help you in your search for an ideal machine learning engineer.  

    • Why do you want to work for us? 
    • What according to you are the qualities a cabin crew should possess? 
    • How do you define yourself? 
    • How do you think the company will be affected positively by hiring you? 
    • What do you think are the major challenges of this job? 
    • How do you think your past experience has helped you for your present role? 
    • Which is your favorite model? Which kind of problems does it solve? 
    • What type of data can it deal with? 
    • Does the model have convergence problems? 
    • What to do if the model is missing data? 
    • How interpretable and quick is the model? 
    • What do you know about EM algorithm? 
    • Tell us about the common algorithms for supervised and unsupervised machine learning. 
    • What do you know about KNN and k-means clustering? What’s the difference between the two? 
    • Where is Bayes’ theorem applicable? 
    • Explain Type 1 and Type 2 error. 
    • Explain ROC and AUC curve. 
    • How are primary and foreign keys related to SQL? 
    • How would you gauge the efficacy of an ML model? 
    • How do you develop a data pipeline? 
    • How do you deal with missing or corrupted data in a dataset? 
    • Tell us about a time when you felt fulfilled with your job? 
    • Defend the remuneration package that you want. 


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