Tag: Uber Engineering
Get to know Uber Aarhus Engineering and the work they do behind the scenes to build and maintain our storage and compute platforms.
As we approach the New Year, Uber Open Source revisits some of Uber Engineering's most popular projects from 2017.
To ring in the New Year, the Uber Engineering Blog shares some of our editor's picks for 2017.
Uber Engineering built Denial by DNS, our open source solution for preventing DoS by DNS outages, to facilitate more reliable experiences on Uber's apps, no matter how users choose to access them.
How does Uber keep New Year's Eve and other high traffic events...well, uneventful? By keeping our networks extensible and our services reliable year-round.
Uber’s Customer Obsession team builds tools that make the customer support experience quicker and more seamless for users across our services.
In this article, we highlight how Uber leverages machine learning and artificial intelligence to tackle engineering challenges at scale.
In this article, members of Uber Bangalore Engineering discuss their role in building reliable transportation systems at scale for India—and beyond.
Uber Engineering built and open sourced NullAway, our fast and practical tool for eliminating NPEs, to help others deploy more reliable Android apps.
Uber Engineering introduces Horovod, an open source framework that makes it faster and easier to train deep learning models with TensorFlow.
Uber Engineering’s Aimee Lucido reflects on how she redefined her career as a software engineer through advocacy and writing.
What did you do this summer? In this article, intern Mitali Palekar reflects on her experience as a member of Uber's Site Reliability Engineering team.
Uber's Roche Janken shares how her background as a dancer influences her approach to privacy engineering.
Uber Engineering introduces a new Bayesian neural network architecture that more accurately forecasts time series predictions and uncertainty estimations.
Uber Engineering introduces Michelangelo, our machine learning-as-a-service system that enables teams to easily build, deploy, and operate ML solutions at scale.