Process
We start with a self-introduction for 5 minutes, then dive deep into ML problems for 20 minutes. Finally, we have 30 minutes for coding (algorithms) and 5 minutes to ask questions.
Questions
Describe your research and how it connected to the next role.
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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
A great place to work, innovate, and have impact
Machine Learning Engineer • Former Employee
Seattle, Washington, United States
April 24, 2025
Pros: Dynamic and friendly team.
Open to innovation and new ideas.
Possible to see your impact in the product.
Cons: Experiences might change depending on the team and manager, but I had a great team and I learned a lot.
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
Ambient Work Culture
Machine Learning Engineer • Current Employee
Gurgaon, Haryana, India
December 14, 2023
Pros: Great to work with some genius minds.
Cons: Not much, it's not that bad.
- 5.0A great place to work, innovate, and have impactMachine Learning Engineer • Former EmployeeSeattle, Washington, United StatesApril 24, 2025Pros: Dynamic and friendly team. Open to innovation and new ideas. Possible to see your impact in the product.Cons: Experiences might change depending on the team and manager, but I had a great team and I learned a lot.
- 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.
- 4.0Ambient Work CultureMachine Learning Engineer • Current EmployeeGurgaon, Haryana, IndiaDecember 14, 2023Pros: Great to work with some genius minds.Cons: Not much, it's not that bad.
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