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Google
Software Engineer Intern
Google·Posted 4 months ago · Sep 2025

Google’s online assessment took me like 5 minutes and it was supposed to be 90, and that’s when I realized they really prioritize your interactions with the interviewer. You absolutely are not going to run any of your code, so if you don’t understand that landscape, you’re going to fail.

Verified4 rounds3 questions
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Labelbox
Forward Deployed Engineer
Labelbox·Posted 3 weeks ago · Aug 2025

The mission and values round felt like some version of, are you ready to work till midnight. If I could not explain exactly why my bug-fix trace was the ground truth, the fanciest deck in the world would have died on the spot.

Verified4 rounds
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Scale AI
Forward Deployed Engineer
Scale AI·Posted 3 weeks ago · Aug 2025

The wild part was that they basically put me through the same bar as software engineering, then only later figured out whether I fit FDE.

Verified5 rounds
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Anthropic
Senior/Staff SWE, Inferencing
Anthropic·Posted 4 months ago · Aug 2025

The main thing is that Anthropic had a very small question bank. When I was interviewing, I already knew the system design question, and the coding questions were like five of them, which was kind of wild.

Verified7 rounds12 questions
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ElevenLabs
Forward Deployed Engineer
ElevenLabs·Posted 4 months ago · Aug 2025

I passed the interviews and it was verbally confirmed, but when the process was finished they decided they only want to hire in SF. Even though I was open to moving, they saw some immigration risks that they didn’t want to continue.

Verified5 rounds4 questions
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OpenAI
Research Engineer
OpenAI·Posted 4 months ago · Jul 2025

The coding plus ML stats round was the hardest by far. They basically asked me to implement an all_gather on noisy nodes, derive how many rounds you’d need for a target error, then figure out a better algorithm using the fact you’re transmitting floats.

Verified6 rounds1 question
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Harvey AI
Principal MLOps Engineer
Harvey AI·Posted 4 months ago · Jul 2025

I ended up pitching this quantum ML architecture where we were training models on quantum hardware to do something as stupidly simple as predict whether a number was even or odd, and Harvey’s panel got weirdly fascinated by the remote coding environment I built for physicists.

Verified5 rounds1 question
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Meta
Product Manager
Meta·Posted 4 months ago · Jul 2025

Culturally, they struck me as much more direct about conflict than my current company. The vibe was state your view, defend it with data, then move on. They also wanted every answer tied back to the company's mission of connecting people, even in the cases that seem far away from social products. I got the sense that internal visibility matters a lot there.

Verified8 rounds7 questions
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Meta
Product Experience Analyst (IC6)
Meta·Posted 4 months ago · Jun 2025

The internal tooling and the data is incredible. When I was there last year, they had their own Meta AI wired into the most commonly used databases, so I could reference tables and column names and just prompt it to give me the query I needed.

Verified8 rounds
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