Your question is Transformer Architecture. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain the transformer architecture.
Asked in the onsite - ML practitioner stage. Explain the major components, trace data through the architecture, and discuss how design choices affect training and inference. Cover self-attention, multi-head attention, positional encoding, feed-forward layers, residual connections, normalization, masking, and encoder-only, decoder-only, and encoder-decoder variants.