J'ai postulé via un recruteur. J'ai passé un entretien chez Amazon (San Diego, CA) en déc. 2021
Entretien
There were 2 technical rounds. Resume shortlisting was skipped because I was contacted by a manager on LinkedIn. Both of the rounds were quite easy. First was DSA, second was ML focused.
Questions d'entretien [1]
Question 1
First round: coding. Basic DS & algo questions Second: Deep dive into past projects and basic ML questions on overfitting, bias/variance, etc
J'ai postulé en ligne. J'ai passé un entretien chez Amazon (Seattle, WA)
Entretien
I went through two rounds of technical interviews. There was no coding at all; instead, I was asked about machine learning theory concepts as well as scenario-based applications and reasoning in ML.
Questions d'entretien [1]
Question 1
Leadership principles / bias variance trade off / gradient explosion
J'ai postulé en ligne. Le processus a pris 4 semaines. J'ai passé un entretien chez Amazon (Sunnyvale, CA) en juil. 2025
Entretien
1st round: Assessment - Easy Data Structure Questions
2nd round: ML Depth - Very detailed, asked about transformers at a root level, Optimization questions on TensorFlowRT, T5 models
3rd round: ML Breadth - Basic ML questions like overfitting/underfitting.
Questions d'entretien [1]
Question 1
How does Multi-headed attention work?
What is serialization?
J'ai postulé en ligne. Le processus a pris 4 semaines. J'ai passé un entretien chez Amazon (San Diego, CA) en janv. 2025
Entretien
Two back to back interviews focussed on breadth followed by depth covering pretty much the entire landscape of machine learning. They also have a lot of Leadership principles questions embedded into the interview. The challenging part is the breadth expectation.