Data / ML

Data / Machine Learning

Backend, Data / ML, Engineering

Cost Efficiency @ Scale in Big Data File Format

January 25, 2022 / Global

Engineering, Data / ML, Uber AI

Capacity Recommendation Engine: Throughput and Utilization Based Predictive Scaling

January 19, 2022 / Global

Data / ML, Engineering

The New Version of Orbit (v1.1) is Released: The Improvements, Design Changes, and Exciting Collaborations

January 11, 2022 / Global

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Stay up to date with the latest from Uber Engineering

Backend, Data / ML, Engineering

How Uber Migrated Financial Data from DynamoDB to Docstore

November 10, 2021 / Global

Backend, Data / ML, Engineering

Introducing uGroup: Uber’s Consumer Management Framework

October 21, 2021 / Global

Backend, Data / ML, Engineering

Improving HDFS I/O Utilization for Efficiency

October 13, 2021 / Global

Backend, Data / ML, Engineering

Real-Time Exactly-Once Ad Event Processing with Apache Flink, Kafka, and Pinot

September 23, 2021 / Global

Data / ML, Engineering

YAML Generator for Funnel YAML Files: Streamlining the Mobile Data Workflow Process

September 16, 2021 / Global

Backend, Data / ML, Engineering

Streaming Real-Time Analytics with Redis, AWS Fargate, and Dash Framework

September 2, 2021 / Global

Backend, Data / ML, Engineering

Enabling Seamless Kafka Async Queuing with Consumer Proxy

August 1, 2021 / Global

Data / ML

How Data Shapes the Uber Rider App

August 26, 2021 / Global

Backend, Data / ML, Engineering

Building Scalable Streaming Pipelines for Near Real-Time Features

August 24, 2021 / Global

Data / ML, Engineering

Efficiently Managing the Supply and Demand on Uber’s Big Data Platform

August 13, 2021 / Global

Data / ML, Engineering

Cost-Efficient Open Source Big Data Platform at Uber

August 11, 2021 / Global

Data / ML, Engineering

Challenges and Opportunities to Dramatically Reduce the Cost of Uber’s Big Data

August 9, 2021 / Global

Data / ML, Engineering

How Uber Achieves Operational Excellence in the Data Quality Experience

August 5, 2021 / Global

Data / ML, Engineering

Pinot Real-Time Ingestion with Cloud Segment Storage

July 29, 2021 / Global

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English ไทย

Data / ML

Cost Efficiency @ Scale in Big Data File Format

Capacity Recommendation Engine: Throughput and Utilization Based Predictive Scaling

The New Version of Orbit (v1.1) is Released: The Improvements, Design Changes, and Exciting Collaborations

Interested in joining Uber Eng?

Stay up to date with the latest from Uber Engineering

How Uber Migrated Financial Data from DynamoDB to Docstore

Introducing uGroup: Uber’s Consumer Management Framework

Improving HDFS I/O Utilization for Efficiency

Real-Time Exactly-Once Ad Event Processing with Apache Flink, Kafka, and Pinot

YAML Generator for Funnel YAML Files: Streamlining the Mobile Data Workflow Process

Streaming Real-Time Analytics with Redis, AWS Fargate, and Dash Framework

Enabling Seamless Kafka Async Queuing with Consumer Proxy

How Data Shapes the Uber Rider App

Building Scalable Streaming Pipelines for Near Real-Time Features

Efficiently Managing the Supply and Demand on Uber’s Big Data Platform

Cost-Efficient Open Source Big Data Platform at Uber

Challenges and Opportunities to Dramatically Reduce the Cost of Uber’s Big Data

How Uber Achieves Operational Excellence in the Data Quality Experience

Pinot Real-Time Ingestion with Cloud Segment Storage

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