Zum Inhalt springenZur Fußzeile springen
  • Jobs
  • Unternehmen
  • Gehälter
  • Für Arbeitgeber

      Deine Karriere auf Höhenflug

      Erfahre, was du verdienen könntest, ergattere deinen Traumjob und tausche dich anonym über dein Berufs- und Privatleben aus.

      employer cover photo
      employer logo
      employer logo

      ONYX InSight

      Ist dies Ihr Unternehmen?

      Info
      Bewertungen
      Vergütung & Zusatzleistungen
      Jobs
      Interviews
      Interviews
      Ähnliche Suchanfragen: Bewertungen für ONYX InSight | Jobs bei ONYX InSight | Gehälter bei ONYX InSight | Zusatzleistungen bei ONYX InSight
      Vorstellungsgespräche bei ONYX InSightMachine Learning Engineer – Vorstellungsgespräche bei ONYX InSightVorstellungsgespräche bei ONYX InSight


      Glassdoor

      • Über uns
      • Auszeichnungen
      • Blog
      • Kontakt
      • Ratgeber

      Arbeitgeber

      • Gratis Arbeitgeberkonto
      • Arbeitgeberbereich
      • Blog für Arbeitgeber

      Informationen

      • Hilfe
      • Richtlinien
      • Nutzungsbedingungen
      • Datenschutz & Anzeigenoptionen
      • Meine Daten nicht verkaufen oder weitergeben
      • Cookie-Zustimmungs-Tool

      Partner werden

      • Werbeanbieter
      App herunterladen

      • Suchen nach:
      • Unternehmen
      • Jobs
      • Standorte

      Copyright © 2008-2026. Glassdoor LLC. „Glassdoor”, „Worklife Pro”, „Bowls” und das Logo sind eingetragene Warenzeichen von Glassdoor LLC.

      Beobachtete Unternehmen

      Verschaffe dir einen Vorsprung bei Chancen und Insider-Tipps, indem du deinem Traumunternehmen folgst.

      Vorstellungsgespräch für eine Beschäftigung als Machine Learning Engineer

      26. März 2019
      Anonymer Bewerber im Vorstellungsgespräch
      Boulder, CO
      Kein Angebot
      Negative Erfahrung
      Schweres Gespräch

      Bewerbung

      Ich habe mich online beworben. Der Vorgang dauerte 2 Monate. Vorstellungsgespräch absolviert im März 2019 bei ONYX InSight (Boulder, CO)

      Vorstellungsgespräch

      I applied around January 25th, 2019 via LinkedIn. Then on February 20th the recruiter reached out via e-mail where he sent me a "knowledge quiz" consisting of 3 parts: 1. a general machine learning part with 6 questions, 2. a predictive maintenance section requiring some in-depth knowledge in mechanical engineering (the posting said nothing about needing to have pre-requisite knowledge in this area) with 7 questions and 3. a machine learning task which I needed to develop. I was given 3 days to complete the "knowledge quiz" (2 of those days were weekdays). Item 1 was straightforward, but items 2 and 3 were far more involved. I had to do quite a bit of research to arrive at answers for item 2. Item 3 was a challenging, long but fun exercise. Completing all 3 items in time was a challenge given the fact that I have a full-time job. After handing in the "knowledge quiz", the recruiter contacted me back on March 6th stating that they were "impressed" with my results and invited me for a Skype interview on March 12th. They then rescheduled the interview twice and they ended up wanting an in-person interview on March 14th. The in-person interview was a 2.5 hour long affair where the interviewers arrived late to the conference room booked for the interview. They also seemed somewhat unprepared. For example, it was supposed to be a conference call with people from all around the world, but the laptop they were connecting through ran out of battery, and had to rush to get a cable for it and connect it back. One of the interviewers kept asking me questions specifically around my PhD (which had nothing to do with the role) in a somewhat rude and grilling manner (he had to leave mid-interview to complete other tasks he had to do). The recruiter was present in the interview but did not participate at all. The bulk of technical questions relevant to the position were made by another remote employee, who asked me scattered questions about my exercise and about general machine learning concepts. If I understood correctly, I did well on this interview, but their main concern was my level of experience for the role, and so asked me in an ambiguous way if I could follow up on my already long machine learning exercise (i.e. try other models and compare with my initial solution), to which I said I could follow up if asked. I then asked questions I had about the company which they answered in a satisfactory way. All of the interviewers except one then started disconnecting/leaving. The remaining interviewer and myself pleasantly chatted for a bit and he told me that he thought that I "would be a very good fit for the role" and showed me around the office, introducing me to several employees and having chats with each. I wrote them an e-mail asking when they wanted me to hand in the follow-up exercise. The aforementioned remote employee answered "How long you think it will take to build a reasonably accurate model?", so I told him I would work on that model over the weekend (it was Thursday night) and hand it in on Monday the 18th of March, as I would be very busy the following week to be able to work on anything other than my job. I then managed to have a functional model ready on Monday the 18th of March and sent it to them with annotations of things to improve and a discussion. On the early morning of Monday the 25th of March I finally got an answer saying that they would be moving forward with another candidate. Because of the level of effort and flexibility I put into this interview, I respectfully replied to get feedback as to what I could have done better. It is still soon after the fact, but I have not yet received a response.

      Fragen im Vorstellungsgespräch [14]

      Frage 1

      Explain some common machine learning concepts (precision, recall, hyperparameter optimization, etc).
      Frage beantworten

      Frage 2

      List error metrics to evaluate a binary classifier.
      Frage beantworten

      Frage 3

      Explain a few methods to handle an imbalanced dataset.
      Frage beantworten

      Frage 4

      Explain how to handle missing or corrupted data in a dataset.
      Frage beantworten

      Frage 5

      Do you have experience with Spark or big data tools for machine learning?
      Frage beantworten

      Frage 6

      Please explain your most successful (first-hand) use cases of machine learning models.
      Frage beantworten

      Frage 7

      For data acquisition, how should sample time and sample rate be treated when collecting vibration data from gears and roller bearings?
      Frage beantworten

      Frage 8

      Describe some reprocessing techniques that could be used for analyzing raw vibration data from variable speed rotating machinery.
      Frage beantworten

      Frage 9

      Describe the spectral characteristics of a bearing fault versus a gear fault.
      Frage beantworten

      Frage 10

      What would be some characteristics to describe a bearing or gear as having a more severe, progressed fault by only looking at the vibration signature?
      Frage beantworten

      Frage 11

      Describe a few ways in which a machine’s power data could be used to assess its health.
      Frage beantworten

      Frage 12

      Describe a few ways to statistically evaluate temperature data from a fleet of machines.
      Frage beantworten

      Frage 13

      SCADA uses alarms and fault codes to notify the operator of the status of a machine. How could these alarms be used for reliability analysis? How could these alarms be used for performance analysis?
      Frage beantworten

      Frage 14

      During the historical data collection period (of some given time series data about wind turbine bearing temperature), several wind turbines had generator bearing problems. Four wind turbines had generator bearing failures and replacements. The symptom of bearing fault is rising temperature beyond normal range. The task is to build the ML model to detect anomaly in generator bearing and identify wind turbines that shows generator bearing defect. You are required to submit the following: List of WT’s that are suspected to have a generator bearing defect during the data period including 4 that had change out, Result showing the reason for diagnosis, and the code associated with the aforementioned. You are then given ids for wind turbines that had NO generator bearing defect (healthy).
      Frage beantworten
      4
      avatar
      Reaktion von ONYX InSight
      6y
      Our employer brand is important to us and we set a high standard in the area of candidate experience. Part of this high standard is providing feedback to applicants who invest their time in the process of applying for a position with us. As a global SME in the EngTech space we are growing fast and experience a high level of interest in our career opportunities. I’m afraid that sometimes this means our limited resources are stretched and we fail to achieve our own high standards. Clearly on this occasion we fell short. We greatly value and acknowledge your comments. Please contact me on steven.mulholland@onyxinsight.com and I will be happy to arrange an opportunity to speak with the hiring team and provide the feedback that is part of our high standard around candidate experience.

      Die besten Unternehmen in der Kategorie „Vergütung & Zusatzleistungen“ in deiner Nähe

      avatar
      Schneider Electric
      4.0★Vergütung & Benefits
      avatar
      bp
      3.9★Vergütung & Benefits
      avatar
      Shell
      3.9★Vergütung & Benefits
      avatar
      Veolia
      3.6★Vergütung & Benefits

      Jobsuchen

      Erhalte personalisierte Jobempfehlungen und Updates, indem du Suchanfragen startest.