Rippling·Machine Learning Engineer·Onsite - System Design / Architecture
May 2026
System design round at Rippling for an MLE role, focused entirely on building out the recommendation and trending pipeline for a news product. Pretty deep dive, no fluff questions, just one long technical problem that kept branching.
- Design the recommendation and trending pipeline for a Google News-style product. Assume article data and user interactions are already available. Cover personalization features, the recommendation architecture, and how trending is computed and served at low latency.
“This one is deceptively broad.” The rest of the author's notes on Machine Learning Engineer interview at Rippling, Onsite - System Design / Architecture round, covers how they worked through the question, what the panel pushed back on, and what they would do differently.
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