Three Approaches to Scaling Machine Learning with Uber Seattle Engineering

Uber's services require real-world coordination between a wide range of customers, including driver-partners, riders, restaurants, and eaters. Accurately forecasting things like rider demand and ETAs enables this coordination, which makes our services work as seamlessly as possible. In an effort to constantly optimize our operations, serve our customers, and train our systems to perform better and better, we leverage machine learning (ML). In addition, we make many of our ML tools open source, sharing them with the community to advance the state of the art. In this spirit, members of our Seattle Engineering team shared their work at an April 2019 meetup on ML and AI at Uber.