Machine Learning Engineer · Onsite · Multiple Types

Amazon — Machine Learning Engineer ❌ Failed

Level: Senior-Level

Round: Onsite · Type: Multiple Types · Difficulty: 5/10 · Duration: 300 min · Interviewer: Unfriendly

Topics: Behavioral Questions, Coding, Machine Learning, CNN, Logistic Regression, Transformer, Attention, Diffusion, Image Generation, LLM, Case Study

Location: Seattle, WA, US

Interview date: 2026-02-15

Got offer: False

Summary

Interview Rounds Overview

• Round 1: Behavioral
• Round 2: Coding
• Round 3: Hiring Manager
• Round 4: ML Breadth
• Round 5: ML Depth

Details

I had a total of 5 rounds for my onsite interview.

Round 1: Behavioral I was asked 3 leadership principle (LP) questions related to: Bias for Action; Have Backbone, Disagree and Commit; Ownership.

Round 2: Coding I solved LeetCode 528. I was also asked 2 LP questions: Deliver Results; Insist on the Highest Standards.

Round 3: Hiring Manager This round covered my background and a deep dive into my projects. I also answered 2 LP questions: Earn Trust; Learn and Be Curious.

Round 4: ML Breadth This round covered traditional ML topics (CNN, logistic regression, etc.). I was asked 1 LP question: Invent and Simplify.

Round 5: ML Depth This round covered transformer, attention, diffusion, image generation, and LLM topics. The case study was on how I would evaluate generation quality (image or text), and if the image is for brand ads, how I would make sure the brand name is right in the image. I was asked 1 LP question: Dive Deep; Think Big.

LeetCode similar: LeetCode 528