Companies rely on machine learning engineers to help design and improve the systems that allow their software to improve on its own, rather than being specifically programmed. During the interview process, be prepared to be tested heavily on both computer science and data science knowledge with an emphasis on recognizing patterns and trends. A bachelor's degree in computer science or a related field will be required.
Python: Version of Python used, and why? Which unit tests have you used on Python projects? Have you used scikit-learn library? Which algorithms have you used from there? What is a list comprehension in python, and how you use it? Are you familiar with "generator comprehension"? What is PEP8? What "pass" does in python? What python libraries have you used? How to resolve inter-dependencies of libraries? What is python "with" statement?
A take home test requiring you to implement a Graph Neural Network on an open ended problem. Some protein dataset with random text added in. They say you shouldn't spend long on it, but this is a non-trivial task.
how would you solve the problems of our comapny?
What is the advantage of training a model from scratch ?
One of the interviewers barely spoke English and got agitated when I pointed that I cannot understand what is he saying.
regression, PCA, degrees and experience
Standard questions about ML algorithms and software development.
What do you understand by casual AI?
Why do you choose to apply for this position?
1. Walk me through your resume 2. What was your thought process for this question in the screening round
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