Engineering

The technology behind Uber Engineering

Engineering, Backend

Upgrading M3DB from v1.1 to v1.5

16 May 2024 / Global

Engineering, Data / ML, Security

DataK9: Auto-categorizing an exabyte of data at field level through AI/ML

9 May 2024 / Global

Engineering, Data / ML, Uber AI

From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey

2 May 2024 / Global

Interested in joining Uber Eng?

Click here

Stay up to date with the latest from Uber Engineering

Uber AI

DragonCrawl: Generative AI for High-Quality Mobile Testing

23 April 2024 / Global

Engineering

Ensuring Precision and Integrity: A Deep Dive into Uber’s Accounting Data Testing Strategies

18 April 2024 / Global

Engineering

Migrating a Trillion Entries of Uber’s Ledger Data from DynamoDB to LedgerStore

11 April 2024 / Global

Engineering, Backend, Data / ML

How LedgerStore Supports Trillions of Indexes at Uber

4 April 2024 / Global

Engineering, Data / ML, Uber AI

Scaling AI/ML Infrastructure at Uber

28 March 2024 / Global

Engineering, Data / ML

Model Excellence Scores: A Framework for Enhancing the Quality of Machine Learning Systems at Scale

21 March 2024 / Global

Engineering, Data / ML

Balancing HDFS DataNodes in the Uber DataLake

14 March 2024 / Global

Engineering, Backend

Load Balancing: Handling Heterogeneous Hardware

7 March 2024 / Global

Engineering, Backend

Network IDS Ruleset Management with Aristotle v2

29 February 2024 / Global

Engineering, Backend, Web

Building Scalable, Real-Time Chat to Improve Customer Experience

20 February 2024 / Global

Engineering, Backend, Data / ML

How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache

15 February 2024 / Global

Engineering, Data / ML

Jupiter: Config Driven Adtech Batch Ingestion Platform

6 February 2024 / Global

Engineering, Backend, Data / ML, Uber AI

DataCentral: Uber’s Big Data Observability and Chargeback Platform

1 February 2024 / Global

Engineering, Backend, Mobile

Stopping Uber Fraudsters Through Risk Challenges

25 January 2024 / Global

Page 5

Select your preferred language

Deutsch English

Sign up to drive

Sign up to ride

Select your preferred language

Deutsch English

Engineering

Upgrading M3DB from v1.1 to v1.5

DataK9: Auto-categorizing an exabyte of data at field level through AI/ML

From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey

Interested in joining Uber Eng?

Stay up to date with the latest from Uber Engineering

DragonCrawl: Generative AI for High-Quality Mobile Testing

Ensuring Precision and Integrity: A Deep Dive into Uber’s Accounting Data Testing Strategies

Migrating a Trillion Entries of Uber’s Ledger Data from DynamoDB to LedgerStore

How LedgerStore Supports Trillions of Indexes at Uber

Scaling AI/ML Infrastructure at Uber

Model Excellence Scores: A Framework for Enhancing the Quality of Machine Learning Systems at Scale

Balancing HDFS DataNodes in the Uber DataLake

Load Balancing: Handling Heterogeneous Hardware

Network IDS Ruleset Management with Aristotle v2

Building Scalable, Real-Time Chat to Improve Customer Experience

How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache

Jupiter: Config Driven Adtech Batch Ingestion Platform

DataCentral: Uber’s Big Data Observability and Chargeback Platform

Stopping Uber Fraudsters Through Risk Challenges

Select your preferred language

Sign up to drive

Sign up to ride

Products

Company

Select your preferred language

Sign up to drive

Sign up to ride