J'ai postulé en ligne. J'ai passé un entretien chez Amazon (Virginia Beach, VA) en févr. 2021
Entretien
hone Interview: Usually, a recruiter will reach out for an initial screening. This involves behavioral questions to assess cultural fit and basic skills. You might be asked about your experience, why you want to work at Amazon, and a brief overview of your background.
Technical Screening: For data-related positions, expect questions on basic statistics, data analysis, and possibly SQL or Python, depending on the role. You may also be asked to solve a problem related to data cleaning, manipulation, or basic analysis.
Looking back, I'm relieved I declined the offer, despite the intense experience. The interview process felt overwhelming, starting with some tough core ML concepts before diving into the LLM fundamentals. During the technical round, I recognized a tokenization question from a PracHub session I had done just a week before. It felt like a small win in an otherwise challenging interview. Ultimately, the pressure and expectations were high, but I felt it wasn't the right fit for me.
Questions d'entretien [2]
Question 1
LLM fundamentals: tokenization design and KL-regularized SFT
There are three rounds in total. The process begins with a coding round, followed by the main interview loop, where you will meet the team and discuss technical skills, experience, and fit.
First round is fun, second round, which is also the final round involved 5 sessions, with different focus. For some sessions, not be able to present my story completely, time was tight, and interviewers were rushing.