DoorDash Machine Learning Engineer Interview Preparation Guide (Junior Level)
Machine Learning Engineer
Doordash
Junior
6 rounds
Updated 11/23/2025
DoorDash's ML Engineer interview process for junior-level candidates spans 4-6 weeks and consists of a recruiter screening, technical phone screen, and 4 comprehensive onsite rounds. The process evaluates technical depth in machine learning and algorithms, practical coding skills, system design thinking, and cultural alignment with DoorDash's ownership-first and experimentation-focused values. Candidates should expect real-world scenarios tied to DoorDash's core use cases such as ETA prediction, fraud detection, and search optimization.
Interview Rounds
1
Recruiter Screening
35 min4 focus topicsculture fit
2
Technical Phone Screen
50 min5 focus topicstechnical
3
Onsite Round 1: ML Coding and Feature Engineering
75 min5 focus topicstechnical
4
Onsite Round 2: Machine Learning Case Study and Design
75 min5 focus topicscase study
5
Onsite Round 3: System Design for ML Infrastructure
60 min5 focus topicssystem design
6
Onsite Round 4: Behavioral Interview and Culture Fit
50 min4 focus topicsbehavioral
Additional Information