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Zillow interview notes, page 2 of 2

Large Enterprises

Screna has 14 Zillow interview write-ups. The most reported round is the technical phone screen (7).

14 interview notes · updated Jul 2026

Zillow·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Zillow product interview with a classic design question that sounds simple but pulls you in a few different directions at once. Not a lot of context given about the role or outcome.
  • How would you improve the airline boarding experience?

“I went straight to the obvious stuff, zones, boarding order, overhead bin space, and then realized I was just listing complaints instead of actually structuring a product answer.”

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Zillow·Machine Learning Engineer·Onsite - System Design / Architecture

Jun 2026
Zillow ML engineer interview with a meaty system design question about RAG pipelines. Just the one question but it went pretty deep into chunking strategy, which I hadn't fully prepped for.
  • You're building a RAG system with an LLM and a vector database. Walk through how you'd design the chunking strategy for documents before creating embeddings, including chunk size, overlap, use of document structure, advanced methods like semantic chunking, and how you'd evaluate and iterate on it.

“This one sprawled in a way I wasn't ready for.”

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Zillow·Machine Learning Engineer·Technical Phone Screen

Jul 2026
Zillow ML engineer interview focused heavily on multimodal model training and the differences between reasoning-focused versus standard chat LLMs. Conceptual depth was clearly the priority here, no coding, just talking through trade-offs.
  • When training a multimodal foundation model that handles both text and images or audio, what do you see as the biggest challenges? Pick one or two and go deep.
  • How does a reasoning-focused LLM differ from a standard instruction-tuned chat model, specifically in terms of training objectives, inference behavior like planning and tool use, and how you'd evaluate reasoning quality?

“I went with modality alignment and data imbalance, which I think was the right call, but I spent too long on the obvious stuff like representation gaps and not enough time on the messier practical issues like how paired data is scarce and noisy.”

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Zillow·Machine Learning Engineer·Onsite - Behavioral / Leadership

Jul 2026
Behavioral screen for an MLE role at Zillow. Three questions, all centered on a single recent project you pick yourself, so the pressure is on you to have a good story ready.
  • Walk me through your background and what you've been focused on lately.
  • Tell me about a recent project you owned end-to-end. What was the goal, your specific role, and what did you actually deliver?
  • What was the hardest problem you ran into on that project, and how did you work through it?

“Pretty standard opener.”

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