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      Búsquedas relacionadas: Opiniones sobre Chronograph | Ofertas de empleos en Chronograph | Sueldos en Chronograph | Beneficios en Chronograph
      Entrevistas de ChronographEntrevistas para el puesto de NLP Engineer en ChronographEntrevista de Chronograph


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      Entrevista de NLP Engineer

      21 ago 2024
      Candidato de entrevista anónimo
      Sin oferta
      Experiencia positiva

      Otras opiniones sobre las entrevistas para el puesto de NLP Engineer en Chronograph

      Entrevista de NLP Engineer

      19 dic 2025
      Candidato de entrevista anónimo
      Sin oferta
      Experiencia positiva
      Entrevista normal

      Solicitud

      Acudí a una entrevista en Chronograph

      Entrevista difícil

      Solicitud

      Envié una solicitud electrónica. El proceso duró 2 meses. Acudí a una entrevista en Chronograph en jul 2023

      Entrevista

      There are 4 rounds with 5 segments 1. HR phone screening: general phone screening questions plus three technical questions (HR just read it aloud) 2. 30-min meeting with the hiring manager: half a deep dive into the resume; half questions related to machine learning practice and problem solving The next two segments are scheduled together 3.1 30-min coding assessment: in Python; hand-craft function to calculate tf-idf 3.2 30-min Paper presentation: read one of the paper they give (from arXiv) and present its content as well as your comments 4. 90 Virtual on site: Mostly behavioral and cultural fit questions; first half chatting with team lead in neighbouring teams (Software, Data engineer); second half with CTO

      Preguntas de entrevista [11]

      Pregunta 1

      (Phone screen) Explain Autoregressive to a layman
      Responder pregunta

      Pregunta 2

      (Phone screen) What is QKV matricies in the NLP context?
      Responder pregunta

      Pregunta 3

      (Phone screen) Why is multi-headed attention so powerful?
      Responder pregunta

      Pregunta 4

      Coding: handcraft TFIDF with only Python built-in libraries
      Responder pregunta

      Pregunta 5

      (Hiring manager) Explain the difference between gradient descent and stochastic gradient descent.
      Responder pregunta

      Pregunta 6

      You have a dataset of 1000 features. You build a baseline model with all features but you are not happy with the performance. You think you need to reduce the features to improve performance, so what methods you can use (to do feature reduction or selection)?
      Responder pregunta

      Pregunta 7

      You have developed a model with appropriate training, validating, and testing. You are about to deploy the model but you still worry that your model overfits. What would you do to check for overfitting? Clarification: by this stage, you still have data not used in the process above
      Responder pregunta

      Pregunta 8

      How to generate vectors from texts? Can you think of any before word2vec?
      Responder pregunta

      Pregunta 9

      Give your definition of a "language model"
      1 respuesta

      Pregunta 10

      Sometimes you need to fine-tune a LLM. How would you do that?
      Responder pregunta

      Pregunta 11

      What is the purpose or advantage of doing A/B testing before deploying the models? Clarification: by A/B test it means the control variable is: with the model or without the model
      Responder pregunta

      Entrevista

      Preliminary phone interview with a Recruiter, followed by a Zoom Call with the hiring manager. Very pleasant and conversationally-focused interview process. While I did not receive an offer, the recruiter was able to provide some post-interview feedback, which I appreciated.

      Preguntas de entrevista [1]

      Pregunta 1

      What experience do you have with fine-tuning various models?
      Responder pregunta