Great place to work for individual contributors
Great place to work for individual contributors
Relatively flat structure. Individuals are greatly empowered. It's a fully profitable company, so no VC rubbish. Compensation is comparable to hedge funds.
Usual growing pains - bullshitters and bean-counters from big tech and consulting sometimes get promoted and put in charge of important decisions, general admin chaos, etc. But nothing that can't be fixed or is annoying enough to leave.
Make sure those who code and contribute move ahead.
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Google Interview Experiences
Machine Learning Engineer
It was good. Focus on arrays, strings, hash maps, trees/graphs, recursion, and dynamic programming. Many candidate guides mention these are common. Practice writing correct, efficient code with good time/space complexity; not just “it works” but “it
Machine Learning Engineer
The interview process involved three rounds: * **Round 1: System Design** This was a creative and fun round to work through. The interviewers were supportive and positive, and I managed to clear this stage. * **Round 2: Theoretical ML/Live
Machine Learning Engineer
The interview process started with a coding round, followed by a technical interview and then an HR round. In the coding round, there were two questions: one on DSA that was of medium-hard difficulty, and another question on machine learning.
Machine Learning Engineer
IndiaNovember 5, 2025It was good. Focus on arrays, strings, hash maps, trees/graphs, recursion, and dynamic programming. Many candidate guides mention these are common. Practice writing correct, efficient code with good time/space complexity; not just “it works” but “it
Machine Learning Engineer
Hyderābād, Telangana, IndiaJuly 31, 2025The interview process involved three rounds: * **Round 1: System Design** This was a creative and fun round to work through. The interviewers were supportive and positive, and I managed to clear this stage. * **Round 2: Theoretical ML/Live
Machine Learning Engineer
IndiaJune 9, 2025The interview process started with a coding round, followed by a technical interview and then an HR round. In the coding round, there were two questions: one on DSA that was of medium-hard difficulty, and another question on machine learning.
