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      Machine Learning Engineer Interview

      17 Apr 2026
      Anonymous interview candidate
      Toronto, ON
      No offer
      Neutral experience
      Difficult interview

      Application

      I applied through a recruiter. The process took 3 weeks. I interviewed at Instacart (Toronto, ON) in Sept 2025

      Interview

      1 round of HR screen, 4 rounds of technical Technical: - ML alg knowledge - Live code - Leetcode style - Case study: they give you a case - Retro study: walk them through a past project

      Other Machine Learning Engineer interview reviews for Instacart

      Machine Learning Engineer Interview

      14 May 2026
      Anonymous interview candidate
      No offer
      Neutral experience
      Easy interview

      Application

      I interviewed at Instacart

      Interview

      The phone screen was surprisingly short, only about 20 minutes, focusing on my background and some general ML concepts. Then came the technical round where I had to design a ranking model for Instacart’s search results. Midway through, it hit me that I had just practiced a very similar problem on PracHub, which made me feel a bit more confident. However, the depth of the discussion, especially around metrics and cold-start items, was intense. In the end, I didn’t receive an offer, but it was a decent experience overall.

      Machine Learning Engineer Interview

      26 Mar 2025
      Anonymous interview candidate
      Toronto, ON
      No offer
      Positive experience
      Average interview

      Application

      I applied through an employee referral. The process took 4 weeks. I interviewed at Instacart (Toronto, ON) in Feb 2025

      Interview

      There are four round in total: 1 code (leetcode easy level) 2 ML concept (focus on fundamental traditional ML stuff) 3 ML system design 4 BQ and project NDA signed for last two rounds. But the recruiter will tell you the expected topic

      Interview questions [1]

      Question 1

      Basic ML concept like l1 l2 norm/loss. concept like recall precision etc.
      Answer question
      1