LinkedIn·Machine Learning Engineer·Technical Phone Screen
Apr 2026
LinkedIn ML engineer technical screen, pretty much a pure deep-learning fundamentals session. No coding, no system design, just someone grilling me on neural net internals for an hour. Came out feeling okay about some of it and genuinely shaky on the optimizer math.
- Walk me through the typical layers in an artificial neural network and what each one does.
- Compare ReLU, sigmoid, SwiGLU, and SiLU as activation functions. When would you actually choose one over another?
- How do you pick a loss function for regression, binary classification, multi-class classification, and ranking tasks?
- Explain how Adam works, specifically the first and second moment estimates, bias correction, and the actual update rule.
“Started fine, input layer, hidden layers, output layer, talked about fully connected vs not.” The rest of the author's notes on Machine Learning Engineer interview at LinkedIn, Technical Phone Screen round, covers how they worked through the question, what the panel pushed back on, and what they would do differently.
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