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      Mistral AI

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      Applied AI Engineer Interview

      Oct 15, 2025
      Anonymous Interview Candidate
      No offer
      Negative experience
      Easy interview

      Application

      I applied through an employee referral. I interviewed at Mistral AI

      Interview

      - I was approached by a Mistral employee on LinkedIn; I was not actively looking for a job at the time, but felt it was worth trying. - First step was a call with this person. - I was then sent various links to resources to best prepare (mostly about LLM evaluation). - Second step was a Python interview, with a focus on refactoring. The interview was not hard for someone with experience in Python, but at times the interviewer did not seem to be too attentive (for example, when I asked if I should use sync or async logic, he asked me in return if I knew what async was; several times he also asked questions and answered them right away without really waiting for my answer). - Third step was a chat about LLM with another Mistral employee; mostly about RAG. The interviewer was nice and open-minded, though at times I could not get them to justify their choices (for example, when discussing RAG vs fine-tuning for a specific use-case, the interviewer was in favor of fine-tuning because "it works better with this use-case," with little further elaboration). - Heard nothing from them for ~10 days, then was invited to the 4th step. Their interview scheduling system is a bit unreliable: most of the time, there are no availabilities, and you have to regularly check the portal in order to hope to book a time. - Fourth step: Python pair programming interview. The interviewer was late and had network issues on their side (not their fault, but worth noting for context). The exercise was about using a third-party API, for information retrieval, in combination with the Mistral API, in order to add the external information/data to the context. The exercise was easy enough to understand, the interviewer made me share my screen to see my IDE. Their network issue made it difficult for them to follow, I could feel they were losing patience at times, and they even had to disconnect from the call a couple of times because of it. In the end, I managed to complete the exercise, even though we could not test the end-to-end result because we did not have a Mistral API key available, making the end goal of the interview a bit unclear. The interviewer wrapped up the interview because of lack of time, and told me they would be in touch. - I received an email the next day telling me the interview process would not continue because my skills when it comes to using APIs were not meeting their expectations. Anyway, without being rude to anyone, most of this process felt like a waste of time. Interviewers were nice people overall, but speaking as someone with experience in tech recruitment, it did feel like each individual step's assessment goal is unclear at best.

      Interview questions [2]

      Question 1

      - Describe what a RAG is?
      Answer question

      Question 2

      - If you have a 2000 page PDF document (i.e. something that does not fit in the context window) that serves as a knowledge base, would you rather fine tune a model or setup a RAG?
      Answer question
      10

      Other Applied AI Engineer Interview Reviews for Mistral AI

      Applied AI Engineer Interview

      May 8, 2026
      Anonymous employee
      Accepted offer
      Positive experience
      Average interview

      Application

      I interviewed at Mistral AI

      Interview

      Very long process but a great learning journey. The prep materials were very deep and technical and a real joy to read. The interviewers were direct but very reasonable to talk to and I had very delightful conversations.

      Applied AI Engineer Interview

      Mar 17, 2026
      Anonymous Interview Candidate
      No offer
      Negative experience
      Easy interview

      Application

      I interviewed at Mistral AI

      Interview

      The recruitment process was hindered by scheduling issues .. Every stage was cancelled and rescheduled multiple times and in one instance, no interviewer showed up for the scheduled slot. The technical stages consisted of a code review, an "LLM quiz," and a live coding session. The LLM quiz covered standard topics - transformer architectures, fine-tuning, and RAG, but the format was a rigid Q&A rather than a technical discussion. It felt as though the interviewer was looking for specific keywords from a prepared sheet rather than exploring depth of understanding. The live coding stage involved using an external API, but was difficult to navigate due to interviewer wifi problems. They joined 10 minutes late with a poor internet connection, which led to communication gaps and frustration when I asked for clarification on the task. The goals of the exercise were not clearly defined, and overall it was hard to understand what was expected. I received a rejection two weeks later via an automated email. The feedback suggested I "work on my deployment skills," which was confusing as deployment was not a component of any of the interview stages. Feels like a shame, I think Mistral may lose many good candidates with a process like this.

      Interview questions [1]

      Question 1

      How do you evaluate RAG?
      Answer question

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