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      KONUX

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      Ricerche correlate: Recensioni su KONUX | Offerte di lavoro di KONUX | Stipendi di KONUX | Benefit di KONUX
      Colloqui di KONUXColloqui per Machine Learning Engineer presso KONUXColloquio di KONUX


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      Colloquio per Machine Learning Engineer

      21 lug 2016
      Candidato anonimo a colloquio
      München, Bavaria
      Nessuna offerta
      Esperienza negativa
      Colloquio difficile

      Candidatura

      Ho presentato la mia candidatura online. La procedura ha richiesto più di una settimana. Ho sostenuto un colloquio presso KONUX (München, Bavaria)

      Colloquio

      I applied through their website. The day after, I received an email from the recruiting manager with a positive feedback from my CV, and straight away a set of machine learning + signal processing tasks along with general questions on machine learning. Having a 1 week deadline without even being warned in advance, I asked for an extension of a couple of days. The tasks were on one hand very interesting because they were related to (if not exactly) the problems the company deals with, but at the same time very lengthy. It took me 3 full days of work to set up and improve the code, certainly more than what is expected from a screening test. During the whole process, I was in contact with a Konux engineer who was quite responsive and helped me understanding the problems better. One week after submitting the solutions, I received a negative feedback from HR. Since I always want to improve myself, given the amount of time spent in the application, and considering the responsiveness of the employees, I asked for feedback. No response, even after pinging them again. Given that the job opening is still there after months, I really wonder if the job interview tasks are just a way to trick applicants to do some work for free.

      Domande di colloquio [1]

      Domanda 1

      Build a machine learning model to map the measurement of three accelerometer time series data with a time series data of an optical sensor
      Rispondi alla domanda
      3

      Altre recensioni di colloqui per Machine Learning Engineer presso KONUX

      Colloquio per Machine Learning Engineer

      13 ago 2016
      Candidato anonimo a colloquio
      Nessuna offerta
      Esperienza negativa
      Colloquio facile

      Candidatura

      Ho presentato la mia candidatura tramite un'altra fonte. La procedura ha richiesto 3 settimane. Ho sostenuto un colloquio presso KONUX nel mese di ago 2016

      Colloquio

      I got referred by someone, and halfway through the hiring process I got contacted by the HR to apply for a job at Konux. They didn't know I was already interviewing there! I visited the office 3 different times to have 4 interviews (inconvenient). In 2 of those I was supposed to meet the CTO, but one time they said he was sick, the other time I started the interview with interviewer X then the CTO joined half an hour late and was constantly looking at his phone for 10 mins then just left, unfortunately he wasn't even listening to the conversation. So I ended up interviewing with X twice. 3 interviews were for knowing about my technical background and other behavioural insights (leadership, conflict resolution..etc). 1 interview was purely technical. The first part involved signal processing questions, the second part was a system design interview but the interviewer was a junior *electrical* engineer so it was very awkward. I had a hard time understanding the questions because the terms used by the interviewer to explain the software system had nothing to do with the SW Eng jargon. Even worse, the questions were asked in a slightly sarcastic/arrogant way. I did not see any senior technical person. Even though some people were really nice, my overall impression was that they're a very young (and arrogant) team who lack a great deal of professionalism, however they're doing a good job in terms of business development and penetrating a very old industry.

      Domande di colloquio [1]

      Domanda 1

      signal processing, machine learning
      Rispondi alla domanda
      2

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