Klaviyo utilizes Ray's open-source framework to enhance data processing, model training, and hyperparameter optimization across large datasets. By employing Ray Data, Ray Train, and Ray Tune, the company streamlines its machine learning workflows, allowing for efficient handling and deployment of models while managing compute costs effectively.

Pinterest has enhanced its machine learning (ML) infrastructure by extending the capabilities of Ray beyond just training and inference. By addressing challenges such as slow data pipelines and inefficient compute usage, Pinterest implemented a Ray-native ML infrastructure that improves feature development, sampling, and labeling, leading to faster, more scalable ML iteration.