# Pinterest Machine Learning Engineer Interview Experiences

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Source: https://www.aced.io/guides/pinterest-machine-learning-engineer-interview/experiences
Source observed: 2026-11-04T22:43:17.927Z
Last checked: 2026-11-04T22:43:17.927+00:00
Indexed: 2026-11-05T21:55:12.272+00:00

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# Pinterest Machine Learning Engineer Interview Experiences

We provide interview-preparation resources through Aced, formerly Exponent. This page contains one candidate-submitted interview experience for the **Pinterest Machine Learning Engineer** role. It is the **Interview experiences** section of our Pinterest Machine Learning Engineer interview guide, alongside the [Expert guide](https://www.aced.io/guides/pinterest-machine-learning-engineer-interview), [Questions](https://www.aced.io/guides/pinterest-machine-learning-engineer-interview/questions), and [Resumes](https://www.aced.io/guides/pinterest-machine-learning-engineer-interview/resumes) sections.

The experience was updated a month ago by Pinterest candidates. The submission was made on **December 5, 2023**, is marked **Older format**, and is labeled **December 2023**.

## Machine Learning Engineer — Pinterest

### Questions asked

- [Design a product recommendation system.](https://www.aced.io/questions/3094)
- [Tell me about a machine learning project you worked on.](https://www.aced.io/questions/3407)
- [For a dataset with a million data points, would you use a DNN or KNN? Why?](https://www.aced.io/questions/3480)
- [Why do you want to work at Pinterest?](https://www.aced.io/questions/3481)
- [Design spam detection on Pinterest.](https://www.aced.io/questions/3482)
- [Explain the differences between nonconvex and convex functions.](https://www.aced.io/questions/3483)
- [Explain the differences between ReLU and Sigmoid.](https://www.aced.io/questions/3484)
- [Where do vanishing gradients occur in a neural network?](https://www.aced.io/questions/3485)
- [Explain data drifting.](https://www.aced.io/questions/3486)
- [Explain overfitting.](https://www.aced.io/questions/3487)
- [Explain regularization.](https://www.aced.io/questions/3488)
- [Implement a k-nearest neighbors algorithm.](https://www.aced.io/questions/3489)

These prompts cover machine-learning system design, project discussion, model selection, motivation, spam detection, mathematical concepts, neural-network behavior, data drift, overfitting, regularization, and implementation of k-nearest neighbors.

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