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      Ricerche correlate: Recensioni su DeepL | Offerte di lavoro di DeepL | Stipendi di DeepL | Benefit di DeepL
      Colloqui di DeepLColloqui per Research Scientist presso DeepLColloquio di DeepL


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      Colloquio per Research Scientist

      10 mag 2023
      Candidato anonimo a colloquio
      Köln
      Nessuna offerta
      Esperienza neutra
      Colloquio difficile

      Candidatura

      Ho presentato la mia candidatura online. La procedura ha richiesto 3 settimane. Ho sostenuto un colloquio presso DeepL (Köln) nel mese di feb 2023

      Colloquio

      It was remote. I applied on LinkedIn and then got an additional form via an email which I also filled. After a few weeks I had an interview scheduled for the following week. The interview was remote, I was told step one is a remote interview about general skills and the second step would be a more technical interview and, likely, on site. The interview began with some easy Python questions. There were some C++ vs Python memory management questions, but not to great detail. Then the focus shifted solely towards Python. They included garbage collection, differences between tuples, lists, and sets and how they are saved in memory. Afterwards, they started asking more about the neural network part. I got questions about Convolutional Neural Network architecture and standard activation functions. Then they started asking about likelihoods, and to be honest, what was annoying was that they weren't asking complicated things, but they clearly had an idea of what I should answer. This is not a format I like, I would like them to give me a question and allow me to explain it, rather than slowly attempt to guide me towards their wanted answer. The second question was something I liked more, about ADAM working principle and advantages over regular gradient descent. The last question was about gradient backpropagation. Basically, I had to explain a few steps of backpropagation and answer a situation where some weights are much larger than others weights.

      Domande di colloquio [6]

      Domanda 1

      C++ vs Python garbage collector
      Rispondi alla domanda

      Domanda 2

      Showed some pieces of code via shared screen for lists, tuples and sets and asked what would happen if the code was executed
      Rispondi alla domanda

      Domanda 3

      Difference between list, set and tuple in python (also memory wise)
      Rispondi alla domanda

      Domanda 4

      Drew a convolutional neural network and said how would you make an output that classifies the input into DOG and CAT + more categories. Asked about activation funcs, likelihoods etc. Wasn't sure what was the purpose of this question.
      Rispondi alla domanda

      Domanda 5

      ADAM: what is it, why is it better than gradient descent, the math behind it etc.
      Rispondi alla domanda

      Domanda 6

      backpropagation, imagine a feed forward neural network with two neurons and they asked what happens if one neuron has a very large weight and the other a very small one (approx 0, but not 0)
      Rispondi alla domanda
      17

      Altre recensioni di colloqui per Research Scientist presso DeepL

      Colloquio per Research Scientist

      17 apr 2026
      Candidato anonimo a colloquio
      Nessuna offerta
      Esperienza neutra
      Colloquio nella media

      Candidatura

      Ho sostenuto un colloquio presso DeepL

      Colloquio

      The whole intrview process was professional and well organanized. All of the interviewers were very polite and friendly. They also have an AI note taker in each interview. I had 3 intervews with them overall. The first one was with a member of their talent acquisition team who also asked some unexpected random python questions!! The second interview was about general machine learning and python understanding, Questions like what happens if we run this or the difference between data structures. The third interview was about live python coding, solving some NLP problems and also guessing the outputs of some python scripts. I got rejected after the third coding interview even though I did solved the main challange and answered most of the other questions correcly. I guess they have to filter the candidates from the pool somehow, but it seems like they dont consider your new role or your prior experience when evaluating your coding. The main issue i see is the fact that in each stage there is only one person evaluating your skills. So at the end I had feedbacks like 1. we are impressed by your deep learning skills. 2. your python is not good enough. I dont blame them for selecing the top ones but good deep learning skills usually dont come for free.

      Domande di colloquio [1]

      Domanda 1

      1. Difference between list, tuple, arrays, how they are stored in memory and which is is faster. 2. given a simple NN, what happens if output variance is too high? how to solve this? how to compute the gradient by hand, making sure you know the basic knowledge behind backprop. 3. given some string like ((1+(3+8))+((7+8)*2)) write a python code to compute the final output.
      Rispondi alla domanda

      Colloquio per Research Scientist

      25 mag 2025
      Candidato anonimo a colloquio
      Köln
      Nessuna offerta
      Esperienza neutra
      Colloquio difficile

      Candidatura

      La procedura ha richiesto 6 settimane. Ho sostenuto un colloquio presso DeepL (Köln)

      Colloquio

      1. Phonecall 2. Interview (general machine learning related questions) 3. Interview (code session - very basic Python questions) 4. Multiple interviews after each other (AC like). ML theory and coding.

      Domande di colloquio [1]

      Domanda 1

      The impact of weight initialization on training.
      Rispondi alla domanda

      Colloquio per Research Scientist

      29 apr 2025
      Candidato anonimo a colloquio
      Berlino
      Nessuna offerta
      Esperienza positiva
      Colloquio difficile

      Candidatura

      Ho sostenuto un colloquio presso DeepL (Berlino)

      Colloquio

      It was a very pleasant experience. We had a great discussion about many DL-related topics. One was a bit long, but overall, it was good. The interviewers were very friendly and guided the whole process well.

      Domande di colloquio [1]

      Domanda 1

      Things about network initialization, coding problems for strings, translation related questions and similar.
      Rispondi alla domanda
      avatar
      Risposta di DeepL
      8mo
      Thank you for sharing your feedback about your interview experience at DeepL. We’re delighted to hear that you found the process pleasant and appreciated the friendliness and guidance of our interviewers. We strive to create an engaging and supportive environment during interviews, so it’s great to know this resonated with you. We appreciate your note about the length of one discussion and will take it into consideration as we continue to refine our process. Best of luck in your future endeavors, and thank you again for your thoughtful feedback!

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