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      MachineMetrics

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      Ricerche correlate: Recensioni su MachineMetrics | Offerte di lavoro di MachineMetrics | Stipendi di MachineMetrics | Benefit di MachineMetrics
      Colloqui di MachineMetricsColloqui per Full Stack Engineer presso MachineMetricsColloquio di MachineMetrics


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      3.8★Stipendio e benefit
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      Digital Natives
      4.4★Stipendio e benefit

      Colloquio per Full Stack Engineer

      26 lug 2021
      Candidato anonimo a colloquio
      Nessuna offerta
      Esperienza neutra
      Colloquio nella media

      Candidatura

      Ho presentato la mia candidatura online. La procedura ha richiesto 3 settimane. Ho sostenuto un colloquio presso MachineMetrics nel mese di lug 2021

      Colloquio

      Interview Process: 1. Phone Screen 2. Coding Interview 3. System Design For each step there are some basic introductory questions about background and experience and why you might be a good fit for the company. Technical screen questions in first phone interview like: What are some differences between NoSQL and relational databases? What is Redis? What is MongoDB? Name 3 REST HTTP verbs What is a left outer join?

      Domande di colloquio [2]

      Domanda 1

      Given a JSON file containing an array of objects that represent machine events with the following properties: { companyId machineId timestamp type subtype key value } Question: How long was the machine ACTIVE during the 14:00 hour?
      1 risposta

      Domanda 2

      MachineMetrics MachineMetrics is an Industrial IoT SaaS company, which basically means that we connect to factory equipment and stream data into the cloud in real time sometimes down to the millisecond level of sampling. We do some in-stream processing and use a variety of database technologies to make this scalable and performant. The data ultimately lands in our cloud (AWS, but not important), and we use it to inform customer-facing applications that provide real-time machine monitoring, in depth reporting and analytics, and advanced applications, such as predictive algorithms that can stop a machine from machining right before critical failure. Automated Workflow System We'd like to build an automated workflow system that can take user-defined logic to fire actions both internal and external to the product. Walk us through how you might approach building out this system, both on the frontend/in the app itself, as well as on the API side and backend servers etc. Some examples of what we'd like to be able to configure are seen below. Example A: When my machine is idle for more than 5 minutes, send a text message and email to the maintenance department Example B: When the machine spindle speed exceeds a certain threshold OR the 5-minute average spindle speed is above a threshold, reject all parts made within a 10 minute window and send a web hook to our QA software.
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