Feb. 10, 2022, 5:30 p.m. | Xinyu Hu

AI – Uber Engineering Blog www.uber.com

At Uber, magical customer experiences depend on accurate arrival time predictions (ETAs). We use ETAs to calculate fares, estimate pickup times, match riders to drivers, plan deliveries, and more. Traditional routing engines compute ETAs by dividing up the road network …


The post DeepETA: How Uber Predicts Arrival Times Using Deep Learning appeared first on Uber Engineering Blog.

ai artificial intelligence deep learning learning machine learning uber

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

IT Commercial Data Analyst - ESO

@ National Grid | Warwick, GB, CV34 6DA

Stagiaire Data Analyst – Banque Privée - Juillet 2024

@ Rothschild & Co | Paris (Messine-29)

Operations Research Scientist I - Network Optimization Focus

@ CSX | Jacksonville, FL, United States

Machine Learning Operations Engineer

@ Intellectsoft | Baku, Baku, Azerbaijan - Remote

Data Analyst

@ Health Care Service Corporation | Richardson Texas HQ (1001 E. Lookout Drive)