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.
Machine Learning Consultant Interview Questions
8,210 machine learning consultant interview questions shared by candidates
Questions regarding ambitions and goals. Technical questions involved a good knowledge of machine learning tools, particularly neural nets and dataset representations
After the test, I feel like it seems like two easy level leetcode problems. But with camera and mic on, I was kind of nervous in the first place. The description of the problem is long, but can be concluded into very short sentence. Finish both but only one get to run correctly, the first one cost me some time.
Binary search, recursion, linear regression, recommendation system
Linear Algebra Time and memory complexity of neuro-network
Tell me about deep learning
Write a function to find connected components of an undirected graph.
What are the algorithms used in machine learning
Code pairing round involved solving some failing test cases and implementing a machine learning based solution on a problem
- 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.
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