Process
Standard CodeSignal OA:
Consists of 4 questions to be completed in 70 minutes. It is proctored, requiring a webcam, microphone, and valid identification for verification.
- 1 LeetCode Easy
- 2 LeetCode Medium
- 1 LeetCode Hard
Questions
String and array manipulation, data structures and algorithms.
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Interview Statistics
The following metrics were computed from 13 interview experiences for the Uber Machine Learning Engineer role in United States.
Success Rate
0%
Pass Rate
Uber's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive38%
Neutral8%
Negative54%
Candidates reported having negative feelings for Uber's Machine Learning Engineer interview process in United States.
Uber Work Experiences
5.0
Growth Good, Management Shaky
Machine Learning Engineer • Current Employee
San Francisco, California, United States
November 5, 2024
Pros: Takes care of career growth.
Transparent Growth Trajectory.
Helpful people.
Cons: Management unstable.
Frequent change in long-term goals.
4.0
Decent Pay, Team Culture Varies
Machine Learning Engineer • Current Employee
Seattle, Washington, United States
April 24, 2025
Pros: Good compensation, workload is reasonable, support for temporary remote work. No large layoffs after COVID.
Cons: Culture depends on the team. Start to have a pip policy.
4.0
Positive Experience as ML Engineer
Machine Learning Engineer • Current Employee
Sunnyvale, California, United States
September 27, 2025
Pros: Fast-paced project workflow and freedom to experiment with various approaches.
Cons: Too much involvement from operations.
- 5.0Growth Good, Management ShakyMachine Learning Engineer • Current EmployeeSan Francisco, California, United StatesNovember 5, 2024Pros: Takes care of career growth. Transparent Growth Trajectory. Helpful people.Cons: Management unstable. Frequent change in long-term goals.
- 4.0Decent Pay, Team Culture VariesMachine Learning Engineer • Current EmployeeSeattle, Washington, United StatesApril 24, 2025Pros: Good compensation, workload is reasonable, support for temporary remote work. No large layoffs after COVID.Cons: Culture depends on the team. Start to have a pip policy.
- 4.0Positive Experience as ML EngineerMachine Learning Engineer • Current EmployeeSunnyvale, California, United StatesSeptember 27, 2025Pros: Fast-paced project workflow and freedom to experiment with various approaches.Cons: Too much involvement from operations.
Uber Interview Questions
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