They asked me about some ML cases where we talked about monitoring, scalibility etc. Usual system design stuff with ML add-ons.
Machine Learning Engineer Interview Questions
6,179 machine learning engineer interview questions shared by candidates
Basic reasoning and logical questions
When a normal distribution is said to be skewed
First round was a non-technical but complete assessment of behavioural scenarios, including a few questions on the candidate's long-term professional ambitions, as well as inquisitions on your general knowledge on AI as well as on the company itself. Second round was a technical and knowledge-based interview on many scientific concepts, testing the candidates on both their understanding of classical ML algorithms as well as their knowledge on more recent developments. Your problem solving approach may also be tested through a live-coding challenge. Final round was a technical homework assignment to be completed in a week, and later presented to the team, followed by a Q&A to understand your approach and decisions.
Solve our take-away challenge
Questions regarding ambitions and goals. Technical questions involved a good knowledge of machine learning tools, particularly neural nets and dataset representations
Code pairing round involved solving some failing test cases and implementing a machine learning based solution on a problem
Why do i want to work at CTM
- Pandas: data cleaning exercise - Numpy: 2d array manipulation (rotations, etc) - SQL: not easy if you haven't done those kind of exercises in sql before. Bus and passengers exercise.
What is the difference between K-Means and KNN algorithms, in which situations would they be applicable?
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