Your activations for one long sequence no longer fit on a GPU. Explain context parallelism and ring attention.
Data, tensor, and pipeline parallelism each leave a single sequence's activations on one device, so training past 200k tokens hits a wall none of them can clear. The fourth axis shards the sequence itself, and the interview turns on the communication math.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Data, tensor, and pipeline parallelism each leave a single sequence's activations on one device, so training past 200k tokens hits a wall none of them can clear. The fourth axis shards the sequence itself, and the interview turns on the communication math.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
