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      Infrrd

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      Buscas relacionadas: Avaliações da empresa Infrrd | Vagas da empresa Infrrd | Salários da empresa Infrrd | Benefícios da empresa Infrrd
      Entrevistas da empresa InfrrdEntrevistas do cargo de Machine Learning Intern da empresa InfrrdEntrevista da empresa Infrrd


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      Entrevista para Machine Learning Intern

      8 de fev. de 2021
      Candidato(a) sigiloso(a) à entrevista
      Chicago, IL

      Outras avaliações de entrevista de vagas de Machine Learning Intern da empresa Infrrd

      Entrevista para Machine Learning Intern

      9 de nov. de 2024
      Candidato(a) sigiloso(a) à entrevista
      Nenhuma oferta
      Experiência neutra
      Entrevista com nível médio de dificuldade
      Nenhuma oferta
      Experiência negativa
      Entrevista fácil

      Candidatura

      Candidatei-me online. Fui entrevistado pela Infrrd (Chicago, IL) em jun. de 2019

      Entrevista

      Named Entity recognition problem in first round as a recruiter screen. Second round included python programming round. Interviewer was thoroughly unprofessional and had memorized answers to the questions he had prepared. Even bluntly told me off to come up with a different solution else he'll send a negative feedback, without even analyzing the one I had provided him. At the end of the interview he started showing off on all the machine learning projects at the company and I hadn't left him time to ask machine learning questions. The experience made me chuckle at the end.

      Perguntas de entrevista [1]

      Pergunta 1

      Homework test on named entity recognition. Python round on generators, decorators, slicing, problem using list of maps, list comprehensions.
      Responder à pergunta

      Candidatura

      Fiz uma entrevista na empresa Infrrd.

      Entrevista

      Following a technical assignment was a virtual interview conducted over Zoom, in which I was asked questions about my career goals, Python skills, and domain knowledge for the role I was applying for. I was also briefed about the company and the nature of work along with the responsibilities of the role I was interested in.

      Perguntas de entrevista [1]

      Pergunta 1

      Python function to parse a string and count the occurrences of every word.
      Responder à pergunta
      1

      Entrevista para Machine Learning Intern

      27 de mar. de 2021
      Candidato(a) sigiloso(a) à entrevista
      Oferta recusada
      Experiência positiva
      Entrevista com nível médio de dificuldade

      Candidatura

      Candidatei-me online. Fiz uma entrevista na empresa Infrrd.

      Entrevista

      It was overall pleasant and quite challenging. You must be confident about your machine learning basics. Especially the math behind. Questions about machine learning are quite exhaustive and comprehensive. Try not to be stuck during the interview. If you prepare enough you should be able to pass.

      Perguntas de entrevista [1]

      Pergunta 1

      Including Coding and machine learning.
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      Entrevista para Machine Learning Intern

      8 de set. de 2020
      Candidato(a) sigiloso(a) à entrevista
      Nenhuma oferta
      Experiência neutra
      Entrevista difícil

      Candidatura

      Candidatei-me de outra forma. Fui entrevistado pela Infrrd em ago. de 2020

      Entrevista

      I had no idea I was by default applying for ML intern when I emailed my resume. And more than 2 weeks has passed since the interview and I think it's safe to assume I didn't get the position. 1. HR emailed some prescreening questions like programming languages and expected compensation. 2. An entity recognition challenge to be completed in three days. I was able to solve it and give my analysis (No feedback about this) 3. ML-based technical interview without instructions about contents. I got unprepared bc I was mostly preparing for resume projects and general DS interview questions like what is F1 score, etc.

      Perguntas de entrevista [1]

      Pergunta 1

      We spent some short time in discussing resume projects. But then we spent the rest of time discussing a single ML model in depth. From data formulation, processing to how the model works to regularization methods. So I say you have to at least review the models to a complete graphic level and shallow-ish math equation level in order to answer the questions. (BTW the interviewer will expect a "correct" answer) How Linear regression works? How are the weights updated? How by adding a regularization term can reduce overfitting? (Think mathematically) And questions like how to deal with imbalanced labels? (I provided 2 solutions but the interviewer was expecting something else, and honestly we don't learn that in graduate school...)
      Responder à pergunta