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General Engineering

The Uber Engineering Tech Stack, Part I: The Foundation

Uber’s mission is transportation as reliable as running water, everywhere, for everyone. Here's the first of a two-part series on the tech stack that Uber Engineering uses to make this happen.
Food Discovery with Uber Eats: Recommending for the Marketplace

Food Discovery with Uber Eats: Recommending for the Marketplace

Uber Eats engineers describe how they surface restaurant recommendations in the app using multi-objective optimization to give eaters the most satisfying experience while maintaining the health of the Uber Eats marketplace.
Diagram of fraud prevention workflow

Advanced Technologies for Detecting and Preventing Fraud at Uber

To detect and prevent fraud, Uber brings to bear data science and machine learning, analyzing GPS traces and usage patterns to identify suspicious behavior.
Why We Decided to Rewrite Uber's Driver App

Why We Decided to Rewrite Uber’s Driver App

Uber engineers outline how we came to the resource-intensive decision to rewrite, rather than migrate or update, our driver app.

Rethinking GPS: Engineering Next-Gen Location at Uber

Uber’s Sensing, Inference, and Research team released a software upgrade for GPS on Android phones that significantly improves location accuracy in urban environments.

How We Built Uber Engineering’s Highest Query per Second Service Using Go

How the Go programming language helped Uber Engineering build and scale our highest queries per second microservice, for geofence lookups.

The Uber Engineering Tech Stack, Part II: The Edge and Beyond

The end of a two-part series on the tech stack that Uber Engineering uses to make transportation as reliable as running water, everywhere, for everyone, as of spring 2016.
Query understanding article feature image

Food Discovery with Uber Eats: Building a Query Understanding Engine

Uber engineers share how we process search terms for our Uber Eats service, using query understanding and expansion to find restaurants and menu items that best match what our eaters want.
Model flow showing rider and driver sign-ups

Why Financial Planning is Exciting… At Least for a Data Scientist

In this article, Uber’s Marianne Borzic Ducournau discusses why financial planning at Uber presents unique and challenging opportunities for data scientists.
World map with stack of gold coins

Transforming Financial Forecasting with Data Science and Machine Learning at Uber

Uber developed its own financial planning software, relying on data science and machine learning, to deliver on-demand forecasting and optimize strategic and operations decisions.
How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats

How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats

Using GPS and sensor data from Android phones, Uber engineers develop a state model for trips taken by Uber Eats delivery-partners, helping to optimize trip timing for delivery-partners and eaters alike.

uReplicator: Uber Engineering’s Robust Apache Kafka Replicator

Take a look into uReplicator, Uber’s open source solution for replicating Apache Kafka data in a robust and reliable manner.

How Uber Engineering Evaluated JSON Encoding and Compression Algorithms to Put the Squeeze on...

Imagine you have to store data whose massive influx increases by the hour. Your first priority, after making sure you can easily add storage capacity, is to try and reduce the data’s footprint to save space. But how? This is the story of Uber Engineering’s comprehensive encoding protocol and compression algorithm test and how this discipline saved space in our Schemaless datastores.

How Ringpop from Uber Engineering Helps Distribute Your Application

How to develop with Uber Engineering's Ringpop, an open source library developed to make our applications cooperative and scalable.

Uber Case Study: Choosing the Right HDFS File Format for Your Apache Spark...

Uber's Maps Collection and Reporting (MapCARs) team shares best practices when choosing which HDFS file formats are optimal for use with Apache Spark.

Engineering Uber’s Next-Gen Payments Platform

During a September 2018 meetup, Uber's Payments Platform team discusses how this technology supports our company's growth through an active-active architecture, exactly-once payment processing, and scalability across businesses.

Best Practices for Unit Testing in React Version 16

Uber ATG Web Platform intern Anat Kleiman shares her advice for testing React version 16 components when altering application logic.
Web-based Uber app

Building a More Seamless Web Booking Flow for Uber

We redesigned Uber's web-based booking flow for riders who prefer a browser over the app, simplifying pickup options and speeding up interactivity.
Summer 2018 Uber Eng Interns

Out of the Classroom: A Snapshot of Uber’s Summer 2018 Interns

A few of Uber's over 200 engineering interns from this year's summer program talk about the projects they worked on and what their experiences in the office were like.
Enhancing the Quality of Uber’s Maps with Metrics Computation - feature image

Enhancing the Quality of Uber’s Maps with Metrics Computation

Maps make up the bedrock of Uber's transportation solutions. Find out how we ensure the quality of our map data through extensive metrics computation, maintaining fidelity to real world locations and pinpointing allowable pick up and drop off locations for riders.

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