Process
I wrote code in Codility and answered 3 easy algorithm questions. I think I wrote my code really well, and I got a score of 92/100. I still haven't heard from them after more than 12 days. I am going to decline their offer.
Questions
I don't remember the exact questions, but they were easy algorithm questions.
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Interview Statistics
The following metrics were computed from 5 interview experiences for the Tempus Machine Learning Engineer role in United States.
Success Rate
0%
Pass Rate
Tempus's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive40%
Neutral40%
Negative20%
Candidates reported having good feelings for Tempus's Machine Learning Engineer interview process in United States.
Tempus Work Experiences
5.0
ML in Tempus
Machine Learning Engineer • Current Employee
New York, New York, United States
April 4, 2025
Pros: Nice colleagues, impactful projects, rich data.
Cons: Unstable stock, lower payment compared to other AI companies.
4.0
Interesting work, but hard to grow
Machine Learning Scientist • Current Employee
March 26, 2025
Pros: Impactful work and fast-paced projects
Cons: Very hard to get promoted or salary increases.
3.0
Good People, Unclear Goals
Engineer • Current Employee
Chicago, Illinois, United States
August 11, 2024
Pros: Good people to work with.
Cons: It is hard to tell what the goals are, and the pay could be better.
- 5.0ML in TempusMachine Learning Engineer • Current EmployeeNew York, New York, United StatesApril 4, 2025Pros: Nice colleagues, impactful projects, rich data.Cons: Unstable stock, lower payment compared to other AI companies.
- 4.0Interesting work, but hard to growMachine Learning Scientist • Current EmployeeMarch 26, 2025Pros: Impactful work and fast-paced projectsCons: Very hard to get promoted or salary increases.
- 3.0Good People, Unclear GoalsEngineer • Current EmployeeChicago, Illinois, United StatesAugust 11, 2024Pros: Good people to work with.Cons: It is hard to tell what the goals are, and the pay could be better.
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