DoorDash ML Engineer Interview Preparation Guide - Entry Level
Machine Learning Engineer
Doordash
entry
7 rounds
Updated 11/23/2025
DoorDash's ML Engineer interview process for entry-level candidates consists of 7 distinct stages spanning 4-6 weeks. The process 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 an ML case study or take-home assignment demonstrating real-world problem-solving. The onsite loop consists of 4 rounds: ML technical depth, coding/algorithms proficiency, foundational ML system design, and behavioral/cultural fit assessment. DoorDash emphasizes ownership, rapid experimentation, and end-to-end ML ownership from feature engineering through production deployment.
Interview Rounds
1
Recruiter Screening
30 min4 focus topicsbehavioral
2
Technical Phone Screen
60 min5 focus topicstechnical
3
ML Case Study / Take-home Assignment
180 min5 focus topicscase study
4
On-site Round 1: ML Technical Interview
60 min5 focus topicstechnical
5
On-site Round 2: Coding & Algorithms
60 min5 focus topicstechnical
6
On-site Round 3: ML System Design
60 min5 focus topicssystem design
7
On-site Round 4: Behavioral & Cultural Fit
45 min5 focus topicsbehavioral
Additional Information