Now more than ever, companies are prioritizing the development, implementation, and adoption of artificial intelligence (AI), and machine learning is a core requirement of AI tools.
There is an intense demand for machine learning (ML) engineers, but since it’s a newer field, it’s difficult to know exactly what questions to ask or assessments to offer.
Take a look at our top machine learning engineer interview questions so you can identify (and hire) only the best candidates!
What Skills Should a Machine Learning Engineer Have?
Your machine learning engineer interview questions should acutely assess whether your candidate has the right skills to succeed and innovate at your company. These skills include, but are not limited to, programming languages, data analysis, and critical thinking.
- Programming Language Proficiency: Whether it’s Python or Java, engineers should have strong coding skills in different programming languages. This is a core pillar of writing code for machine learning algorithms and models.
- Data Handling and Analysis: Machine learning algorithms are built on vast data sets, so processing and handling skills are critical.
- Math and Statistics: ML engineers build upon mathematical and statistical analysis to refine algorithms and models.
- Problem-Solving and Critical Thinking: The capabilities of AI and big data are still evolving. ML engineers need strong, out-of-the-box problem-solving and thinking skills to consistently develop new architectures, networks, and frameworks without a “guidebook” to follow.
Top Machine Learning Engineer Interview Questions
Take a look at some common machine learning engineer interview questions you might ask your next candidate.
Technical Questions
- What are the different types of machine learning?
- How do you choose which algorithm to use for a data set?
- How do you determine supervised, unsupervised, or reinforced learning?
- What are support vectors, and when do you use them?
- How do you attack bias in machine learning inputs?
- How do you look at overfitting and underfitting?
- Describe a project where you had to implement a deep learning technique you were unfamiliar with. How did you go about learning about it?
Communication and Teamwork Questions
- Tell us about a time you disagreed with your product or engineering team. How did it go?
- How do you communicate negative feedback or constructive criticism to other engineers?
- How do you describe complex ML concepts to non-technical stakeholders?
- How do you ensure data quality across different teams?
- Tell us about a time you were given a tight deadline. How did you communicate the project constraints?
- Have you ever mentored a new or entry-level team member?
- What strengths do you bring to teams? What are your weaknesses?
Professional Development Questions
- What drove you to the field of machine learning?
- What excites you the most about the future of machine morning?
- How do you stay updated with the latest innovations and advancements in machine learning?
- What is your leadership style, and how do you like to be managed?
- Describe your top three professional values.
- What are your career goals five years from now? How do you plan on achieving them?
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Find Top Machine Learning Engineers with the Right Interview Questions
As your organization works to gain a competitive edge through artificial intelligence and machine learning innovations, ML engineers are a crucial piece of the puzzle. Ask these strategic ML engineer interview questions to learn more about a candidate’s technical knowledge and experience but, more importantly, how they work with complex product and engineering teams.
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