Process
Was sent an object detection mini project. The project consisted of finding star figures in the night sky.
If you break it down to the bone, imagine implementing YOLO but instead of four points for your bounding box, it's five.
Questions
They asked to complete a mini object detection project within a week.
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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
5.0
Amazing ML Team
Senior Machine Learning Engineer • Current Employee
Washington, DC
September 28, 2022
Pros: Highly qualified ML team with many products that are exploding in growth, and interesting research.
Cons: Sometimes it can be a lot of work - especially for people who are highly qualified, but that's to be expected at a smart company.
- 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
- 5.0Amazing ML TeamSenior Machine Learning Engineer • Current EmployeeWashington, DCSeptember 28, 2022Pros: Highly qualified ML team with many products that are exploding in growth, and interesting research.Cons: Sometimes it can be a lot of work - especially for people who are highly qualified, but that's to be expected at a smart company.
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