I was contacted by a recruiter nearly five months after I submitted my application.
The first round was a screening call with the hiring manager, focusing mostly on my previous experience and how it aligned with the team’s needs.
The second round was a technical coding interview with a junior engineer, which went well. I liked that the coding round tested implementation of a specific use case related to the work rather than a random LeetCode question.
Following that, I was invited to a virtual onsite for the third and fourth rounds.
In the third round, I interviewed with someone who didn’t seem to have a clear understanding of how to evaluate candidates. The conversation lacked structure, and the interviewer didn’t seem to engage with or build on my responses. At one point, they asked who had conducted my earlier interview, which felt unprofessional and irrelevant.
In the fourth round, I spoke with a director who appeared disengaged, frequently yawning and asking random questions with little interest in my answers.
Explain the architecture of large language models.
The following metrics were computed from 1 interview experience for the Cerebras Machine Learning QA Engineer role in California.
Cerebras's interview process for their Machine Learning QA Engineer roles in California is extremely selective, failing the vast majority of engineers.
Candidates reported having very negative feelings for Cerebras's Machine Learning QA Engineer interview process in California.