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      Sigmoidal

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      Machine Learning/NLP Engineer Interview

      4 Mar 2025
      Anonymous employee
      Warsaw, Masovia
      Accepted offer
      Positive experience
      Difficult interview

      Application

      I applied through a recruiter. The process took 3 weeks. I interviewed at Sigmoidal (Warsaw, Masovia) in Jun 2022

      Interview

      It started with an initial call with HR with a recruiter (I want to give my best to her; she really took care of me), a senior architect, and a final client interview. It included an offline case study. The overall process took around 2–3 weeks, which felt long, but they were clearly focused on hiring the best ones. Sigmoidal initially reached out to me via LinkedIn. I usually don’t respond to such msgs, but they presented a highly impactful project where I’d design something used by a company with tens of thousands of employees. They also clearly outlined the interview process which made a great first impression. The interviews were challenging and tested technical skills, business understanding, English proficiency, and soft skills. One of the key stages was a take-home use case that combined business understanding with a technical challenge. One of the toughest parts was the in-depth technical interview with one of their architects, an incredibly knowledgeable and hands-on expert. It was probably one of the most challenging technical interviews I’ve ever had, but in the end, it felt rewarding to know I had passed. The final steps happened almost simultaneously. I had a direct call with the account manager, who gave me valuable insights into the project and helped me prepare for the last step - an interview with their client. After that, things moved extremely fast. I had a final call with the recruiter to go over the contract and they were very transparent throughout the process. The salary offer was excellent and I accepted it within ~48 hours.

      Interview questions [1]

      Question 1

      [Use case presented] Would you use vector databases here, or would you go with a different approach? If vector databases, then why?
      Answer question

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