Google DeepMind Robotics Engineer interview experience

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Mountain View, CAPosted Oct 2025 · Candidate report, summarized by Dataford

I went in through a referral, and the process ended up being slower than I expected—at times I waited more than a month to hear feedback after interviews.

The overall difficulty wasn’t described as “wildly” hard, but the set of topics was broad and the standard still felt high.

I had several rounds that mixed Python work with more research-adjacent thinking. The coding interviews were described as surprisingly chill and not trick-leet-code heavy, but I still needed to be quick and explain my approach clearly. There was an ML fundamentals portion covering things like loss functions, classification versus regression, dimensionality reduction, regularization, CNNs, and even RL. The systems design interview was the part that really hurt me: it was

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