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Bea Schuster

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Bea Schuster is a freelance editor and writer for Uber Engineering. When she’s not enhancing engineers’ eloquence, she authors video game narratives and writes multiple choice tests for English classes.

Engineering Blog Articles

Profiles in Coding: Diana Yanakiev, Uber ATG, Pittsburgh

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Self-driving cars have long been considered the future of transportation, but they’re becoming more present everyday. Uber ATG (Advanced Technologies Group) is at the forefront of this technology, helping bring safe, reliable self-driving vehicles to the streets. Of course,

Profiles in Coding: Christabelle Bosson, Uber Elevate, San Francisco

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Uber Elevate takes Uber’s pioneering transportation technology to new heights with urban aerial ridesharing. In its mission to make aviation a part of everyday transportation, Uber Elevate is building an all-electric aerial mobility ecosystem that will bypass congestion on

Celebrating International Women’s Day: Meet the Women Building Uber’s Global Platform

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Around the world, Uber’s technical teams build the platforms that power our dynamic suite of mobility services, from food delivery and freight to ridesharing and scooter rentals. These engineers, data scientists, product managers, program managers, and many other technologists both

Optimizing Observability with Jaeger, M3, and XYS at Uber

When something goes wrong with a piece of code, engineers want to know all the relevant details of the error immediately so they can get right to work remedying the malfunction. 

However, as technology has advanced, measuring system metrics and

Conducting Better Business with Uber’s Open Source Orchestration Tool, Cadence

Uber’s platform consists of many microservices, self-contained sub-applications that support all the features that make up our global services. 

To help our microservices work in harmony, we built Cadence, our orchestration engine. This tool routes requests, directs

Three Approaches to Scaling Machine Learning with Uber Seattle Engineering

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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

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