Stay up to date with the latest from Uber Engineering

Uber AI

Uber AI is at the heart of AI-powered innovation and technologies at Uber. AI research and its applications solve challenges across the whole of Uber.

Engineering, Aarhus, Backend, Uber AI

Cinnamon Auto-Tuner: Adaptive Concurrency in the Wild

December 7, 2023 / Global

Engineering, Data / ML, Uber AI

Risk Entity Watch – Using Anomaly Detection to Fight Fraud

September 28, 2023 / Global

Engineering, Backend, Culture, Uber AI

The Transformative Power of Generative AI in Software Development: Lessons from Uber’s Tech-Wide Hackathon

August 3, 2023 / Global

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Stay up to date with the latest from Uber Engineering

Engineering, Uber AI

Innovative Recommendation Applications Using Two Tower Embeddings at Uber

July 26, 2023 / Global

Engineering, Data / ML, Uber AI

D3: An Automated System to Detect Data Drifts

February 23, 2023 / Global

Engineering, Culture, Data / ML, Uber AI

ML Education at Uber: Program Design and Outcomes

August 2, 2022 / Global

Engineering, Culture, Data / ML, Uber AI

ML Education at Uber: Frameworks Inspired by Engineering Principles

July 28, 2022 / Global

Uber AI, Data / ML, Engineering

Uber’s Highly Scalable and Distributed Shuffle as a Service

July 7, 2022 / Global

Uber AI, Backend, Engineering, Mobile

Uber’s Real-Time Document Check

June 9, 2022 / Global

Uber AI, Backend, Data / ML, Engineering, Mobile

Introducing Carbon Feed for Earners: The One-Stop Info Shop

February 16, 2022 / Global

Uber AI, Data / ML

DeepETA: How Uber Predicts Arrival Times Using Deep Learning

February 10, 2022 / Global

Uber AI, Data / ML, Engineering

Project RADAR: Intelligent Early Fraud Detection System with Humans in the Loop

February 1, 2022 / Global

Engineering, Data / ML, Uber AI

Capacity Recommendation Engine: Throughput and Utilization Based Predictive Scaling

January 19, 2022 / Global

Uber AI, Data / ML, Engineering

Elastic Distributed Training with XGBoost on Ray

July 7, 2021 / Global

Uber AI, Engineering

Fraud Detection: Using Relational Graph Learning to Detect Collusion

May 21, 2021 / Global

Uber AI

Applying Machine Learning in Internal Audit with Sparsely Labeled Data

March 2, 2021 / Global

Uber AI, Engineering

Uber AI

Cinnamon Auto-Tuner: Adaptive Concurrency in the Wild

Risk Entity Watch – Using Anomaly Detection to Fight Fraud

The Transformative Power of Generative AI in Software Development: Lessons from Uber’s Tech-Wide Hackathon

Interested in joining Uber Eng?

Stay up to date with the latest from Uber Engineering

Innovative Recommendation Applications Using Two Tower Embeddings at Uber

D3: An Automated System to Detect Data Drifts

ML Education at Uber: Program Design and Outcomes

ML Education at Uber: Frameworks Inspired by Engineering Principles

Uber’s Highly Scalable and Distributed Shuffle as a Service

Uber’s Real-Time Document Check

Introducing Carbon Feed for Earners: The One-Stop Info Shop

DeepETA: How Uber Predicts Arrival Times Using Deep Learning

Project RADAR: Intelligent Early Fraud Detection System with Humans in the Loop

Capacity Recommendation Engine: Throughput and Utilization Based Predictive Scaling

Elastic Distributed Training with XGBoost on Ray

Fraud Detection: Using Relational Graph Learning to Detect Collusion

Applying Machine Learning in Internal Audit with Sparsely Labeled Data

Ludwig v0.3 Introduces Hyperparameter Optimization, Transformers and TensorFlow 2 support

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