J'ai postulé via la recommandation d'un employé. Le processus a pris 4 semaines. J'ai passé un entretien chez Amazon (Canada, KY) en juin 2021
Entretien
The process was for DS L5 (received at the end) and started by a referral. The entire process took about 4 weeks. Screen with the recruiter (0.5 hrs). Chat about my background, what I’m looking for in the next role and why am I applying now. Do not underestimate initial phone screens in general. I have gone into some calls unprepared thinking that my resume speaks for itself, having this “I’m in demand” mentality, only to be rejected outright.
Questions d'entretien [1]
Question 1
Some questions can also be presented in the form of a simple case exercise such as how would you process a dataset for training and how would you decide what model to use. Interviewers at all rounds will always ask follow-up questions to your answers so if you suggest an idea or approach, be sure you are familiar with it. They may also ask you about keywords you wrote on your resume. For example, if you wrote “GANs” somewhere on your resume, don’t be surprised if they ask you to explain GANs to them in detail with a bunch of follow-up questions. Make sure you brush up on fundamentals of ML and statistics
Science Case study
Describe how you will generate your dataset: how you will select an unbiased sample, deal with class imbalance, consider temporal effects. How will you split into train/val/test?
I follow this website: https://mlengineer.io/
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.
Thrilled to have accepted the offer — the process was tougher than I expected. The first round was primarily technical, where I tackled an A/B testing design question that required detailed metrics and sample size calculations. Later, I faced a SQL query challenge focused on tracking customer purchases over consecutive months. Funny enough, I had spent quite some time on PracHub digging into similar case studies, which really helped me approach these problems confidently. The final round included behavioral questions, and I felt well-prepared overall.