Process
I applied through a recruiter. The recruiter was very helpful and accommodating.
After the recruiter screen, I had one LeetCode-style coding round. The question was easy and was related to probability. Then there was a behavioral interview: around 15 questions in 40 to 50 minutes, so I had to quickly answer. The recruiter was quickly moving to another question, so don't just prepare 4 to 5 scenarios, but as many as you can. Be natural and discuss real scenarios.
Then there was another LeetCode-style interview. The problem was graph-based, medium to hard, and I couldn't solve it at all. It was a Union Find problem. Then there was another LeetCode round: a medium to hard problem. It was DP with optimisation and had alphabets involved.
Overall, the experience was very pleasant, and the interviewers were helpful.
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Interview Statistics
The following metrics were computed from 43 interview experiences for the Google Machine Learning Engineer role.
Success Rate
Google's interview process for their Machine Learning Engineer roles is extremely selective, failing the vast majority of engineers.
Experience Rating
Candidates reported having very good feelings for Google's Machine Learning Engineer interview process.
Google Work Experiences
- 5.0Awesome place to workMachine Learning Engineer • Former EmployeeLondon, England, United KingdomNovember 2, 2020Pros: Good place to work and nice people to work with.Cons: A really good place, too comfortable. ☺️
- 4.0Good company to work withMachine Learning Engineer • Former EmployeeBengaluru, Karnataka, IndiaAugust 31, 2024Pros: Good salary with many other extra benefits.Cons: Slowly, the work-life balance is decreasing.
- 4.0Great experience in this companyMachine Learning Engineer • Current EmployeeMay 29, 2022Pros: The company is working on interesting projects.Cons: Roles in the company are well defined, so there's less exposure to other roles.
Google Interview Questions
