DoorDash Machine Learning Engineer Interview Preparation Guide - Mid Level
Machine Learning Engineer
Doordash
Mid Level
7 rounds
Updated 11/23/2025
DoorDash's Machine Learning Engineer interview process follows a structured approach spanning 5-8 weeks. It begins with a recruiter screening to assess background and motivation, followed by a technical phone screen evaluating coding fundamentals and ML concepts. Candidates then complete a take-home assignment or live working session demonstrating end-to-end ML project capabilities. The on-site phase (4 rounds) assesses technical depth through coding and algorithm challenges, system design for scalable ML infrastructure, real-world ML case studies with data analysis, and behavioral fit aligned with DoorDash's ownership-first and experimentation-driven culture.
Interview Rounds
1
Recruiter Screening
40 min5 focus topicsculture fit
2
Technical Phone Screen
60 min5 focus topicstechnical
3
Take-Home Assignment or Live Working Session
300 min6 focus topicscase study
4
On-site Round 1: ML Coding and Algorithm Design
60 min5 focus topicstechnical
5
On-site Round 2: System Design for Machine Learning
60 min5 focus topicssystem design
6
On-site Round 3: ML Case Study and Data Analysis
90 min6 focus topicscase study
7
On-site Round 4: Behavioral and Cultural Fit
45 min6 focus topicsbehavioral
Additional Information