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On the move in Trinidad and Tobago

Things to do and ways to get there

Engineering, Backend, Data / ML

How Uber Accomplishes Job Counting At Scale

22 May 2024 / Global

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

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Engineering, Data / ML, Uber AI

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

2 May 2024 / Global

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

Transit

Case study: Tri-Rail’s role in paving the way for effortless commuting

14 February 2024 / Global

Transit

On the move in Trinidad and Tobago

Things to do and ways to get there

How Uber Accomplishes Job Counting At Scale

Upgrading M3DB from v1.1 to v1.5

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

Get a ride when you need one

Start earning in your city

Get a ride when you need one

Start earning in your city

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

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

Case study: Tri-Rail’s role in paving the way for effortless commuting

Public transport agencies trial mixed fleets to implement local on-demand transport

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