Machine Learning Engineer Interview Experience - United States
February 1, 2020
Neutral ExperienceNo Offer
Process
I had three stages before being rejected:
- Interview with a recruiter
- Take-home machine learning test
- Technical coding interview - surprisingly, they asked about stochastic processes, which threw me off guard. They didn't even bother to ask me about the take-home, which I totally rocked.
Questions
Estimating probability distributions for certain properties of other distributions. Like estimating the distance between two variables of sorted samples of a uniform distribution.
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Interview Statistics
The following metrics were computed from 23 interview experiences for the Scale AI Machine Learning Engineer role in United States.
Success Rate
4%
Pass Rate
Scale AI's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive30%
Neutral35%
Negative35%
Candidates reported having mixed feelings for Scale AI's Machine Learning Engineer interview process in United States.
Scale AI Work Experiences
5.0
High-Achieving Place with Great People!
Machine Learning Engineer • Current Employee
San Francisco, CA
September 13, 2022
Pros: - Insanely smart people
- Great career trajectories
- Company growth that is out of this world
- Inspiring CEO
- Friendly culture
Cons: Not many people do work hard, but it is worth it.
2.0
Gigantic Annotation Pipeline
Machine Learning Engineer • Current Employee
San Francisco, CA
June 25, 2025
Pros: Work with frontier labs
* Fast growing environment
* Potential fast career growth
Cons: Possible shipwreck due to Meta’s acquisition
1.0
Watch Out
Software Engineer • Current Employee
San Francisco, CA
May 25, 2025
Pros: Lots of opportunities to learn and grow. A great place to be from.
Cons: Work-life balance. Values speed over quality in excess.
- 5.0High-Achieving Place with Great People!Machine Learning Engineer • Current EmployeeSan Francisco, CASeptember 13, 2022Pros: - Insanely smart people - Great career trajectories - Company growth that is out of this world - Inspiring CEO - Friendly cultureCons: Not many people do work hard, but it is worth it.
- 2.0Gigantic Annotation PipelineMachine Learning Engineer • Current EmployeeSan Francisco, CAJune 25, 2025Pros: Work with frontier labs * Fast growing environment * Potential fast career growthCons: Possible shipwreck due to Meta’s acquisition
- 1.0Watch OutSoftware Engineer • Current EmployeeSan Francisco, CAMay 25, 2025Pros: Lots of opportunities to learn and grow. A great place to be from.Cons: Work-life balance. Values speed over quality in excess.
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