Amazon Machine Learning Engineer Interview Preparation Guide - Entry Level
Machine Learning Engineer
Amazon
entry
7 rounds
Updated 11/23/2025
Amazon's Machine Learning Engineer interview process for entry-level candidates follows a structured progression designed to assess technical depth, problem-solving ability, and alignment with Amazon's leadership principles. The process includes initial recruiter screening, two technical phone screens covering coding fundamentals and ML concepts, followed by four onsite rounds evaluating coding, ML theory, system design, and behavioral alignment. Each round targets different dimensions of the role and the interviewer feedback directly influences hiring decisions.
Interview Rounds
1
Recruiter Screening
30 min5 focus topicsculture fit
2
Technical Phone Screen - Coding Fundamentals
60 min5 focus topicstechnical
3
Technical Phone Screen - Machine Learning Fundamentals
60 min6 focus topicstechnical
4
Onsite Round 1 - Coding and Algorithms
60 min4 focus topicstechnical
5
Onsite Round 2 - Machine Learning Fundamentals and Theory
60 min6 focus topicstechnical
6
Onsite Round 3 - Machine Learning System Design
60 min5 focus topicssystem design
7
Onsite Round 4 - Behavioral and Amazon Leadership Principles
60 min6 focus topicsbehavioral
Additional Information