TomTom Deep Learning R&D Engineer interview questions
Updated 14 Mar 2019
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Deep Learning R&D Engineer applicants have rated the interview process at TomTom with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 54.6% positive. This is according to Glassdoor user ratings.
Common stages of the interview process at TomTom as a Deep Learning R&D Engineer according to 1 Glassdoor interviews include:
Phone interview: 100%
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Had an initial screening followed by two rounds of technical interviews. Each interview included live coding in C++ and Python. Didnt make it to the last round which was an onsite interview.
Interview questions [1]
Question 1
A lot basic ML and DL questions. Spanning from KMeans to GMM, different optimizers used in deep learning, choice of activation functions