What makes Mixture-of-Experts models hard to train, and how do you handle routing, load balance, and all-to-all?
MoE gives you more parameters for the same FLOPs, but the gating network, the load imbalance, and the all-to-all shuffle bring failure modes dense models never see. Here is the training playbook.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
MoE gives you more parameters for the same FLOPs, but the gating network, the load imbalance, and the all-to-all shuffle bring failure modes dense models never see. Here is the training playbook.
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.
