Design an online experimentation (A/B testing) platform for ML models at scale.
A trustworthy experiment platform is far more than a 50/50 split. The signal is consistent assignment, exposure logging, statistical rigor, and guardrails that survive peeking and sample-ratio mismatch. Here is the design.
Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.
A trustworthy experiment platform is far more than a 50/50 split. The signal is consistent assignment, exposure logging, statistical rigor, and guardrails that survive peeking and sample-ratio mismatch. Here is the design.
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.