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      Cerebras (CA)

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      Cerebras (CA) interviews FAQs

      • Common stages of the interview process at Cerebras (CA) as a Senior AI Engineer according to 1 Glassdoor interviews include:

        One on one interview:  50%

        Skills test:  50%

      • Here are the most commonly searched roles for interview reports -

        1. Member Of Technical Staff(17) ;
        2. Member of Technical Staff(MTS)(8) ;
        3. Software Engineer(4) ;
        4. Compiler Engineer(2) ;
        5. Engineer(2) ;
        6. Intern(2) ;
        7. Machine Learning Engineer(2) ;
        8. Senior Member of Technical Staff(2) ;
        9. Software Engineer Intern(2) ;
        10. Software Engineering Intern(2) ;
        11. Software Intern(2) .


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      Jobs at Cerebras (CA)

      25 jobs in United States
      Principal SRE - AI Inference
      Sunnyvale, CA
      ·
      $171K - $237K /yr
      (Glassdoor est.)
      View job
      Senior Performance Engineer, Inference
      Sunnyvale, CA
      ·
      $138K - $198K /yr
      (Glassdoor est.)
      View job
      Sr./Staff TPM - Inference Capacity
      Sunnyvale, CA
      ·
      $71K - $126K /yr
      (Glassdoor est.)
      View job
      Sr. Technical Staff
      Sunnyvale, CA
      ·
      $127K - $190K /yr
      (Glassdoor est.)
      View job
      Principal Engineer, Inference Cloud
      Sunnyvale, CA
      View job

      Senior AI Engineer Interview

      Jun 19, 2025
      Anonymous Interview Candidate
      Sunnyvale, CA
      No offer
      Negative experience
      Easy interview

      Application

      I interviewed at Cerebras (CA) (Sunnyvale, CA)

      Interview

      I recently had an interview that felt quite easy , yet I was rejected at the end—which honestly left me a bit frustrated and disappointed. There were three technical rounds, and none of them felt particularly challenging. Round 1: Resume Deep Dive & Coding The first round focused on my resume—mainly past projects and experience. They asked me to explain a few things I’d worked on and justify some of the technical decisions I’d made. Then they gave me a fairly basic coding question, which I completed without any issues. Round 2: AI Fundamentals This round was centered around the basics of AI and ML. They asked conceptual questions—like the difference between supervised and unsupervised learning, overfitting vs underfitting, and basic algorithm comparisons. It felt like more of a discussion than an evaluation. I answered everything confidently. Round 3: In-Depth AI/ML Discussion The third round went deeper into my understanding of AI/ML. They asked about the architectures I’ve used, hyperparameter tuning strategies, training challenges, model evaluation metrics, etc. Even this round wasn’t too tough—it was very aligned with the work I’ve done in the past. Despite all of that going well, I was rejected. Based on how easy and smooth the rounds were, I can’t help but feel like they had already chosen another candidate and were just interviewing others as a formality—to check a process box or complete internal requirements. It’s disappointing because it didn’t feel like a merit-based outcome.

      Interview questions [1]

      Question 1

      What is regularization? Explain L1 vs L2. How do you evaluate a classification model? What metrics do you prefer and why?
      Answer question
      3
      View all Senior AI Engineer Jobs