Interning at Uber: Building the Uber Eats Menu Scheduler

Jonathan Levi recounts his experience as an intern at Uber during Summer 2018, including building a useful project for the Uber Eats team.

Horovod Joins the LF Deep Learning Foundation as its Newest Project

Horovod, Uber's distributed training framework, joins the LF Deep Learning Foundation to help advance open source innovation in AI, ML, and deep learning.

Open Source at Uber: Meet Alex Sergeev, Horovod Project Lead

We sat down with Horovod project lead, Alex Sergeev, to discuss his path to open source and what most excites him about the future of Uber's distributed deep learning framework.

Scaling Cash Payments in Uber Eats

Scaling Cash Payments in Uber Eats - feature_image
Uber's new driver app leverages its offline mode along with a cash-drop system organized around restaurants so that Uber Eats customers can pay for deliveries with cash.

Faster Neural Networks Straight from JPEG

Uber AI Labs introduces a method for making neural networks that process images faster and more accurately by leveraging JPEG representations.

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data

Part of Uber's open source M3 metrics system, our query engine can support real-time, large-scale computation and multiple query languages.

Introducing Makisu: Uber’s Fast, Reliable Docker Image Builder for Apache Mesos and Kubernetes

Uber built Makisu, our open source Docker image builder, to enable the quick, reliable generation of Dockerfiles in Mesos and Kubernetes ecosystems.

Uber Joins the Linux Foundation’s OpenChain Project as a Platinum Member

As part of the OpenChain Project’s governing board, Uber will help create best practices and define standards for open source software compliance.

Engineering Uber’s Next-Gen Payments Platform

During a September 2018 meetup, Uber's Payments Platform team discusses how this technology supports our company's growth through an active-active architecture, exactly-once payment processing, and scalability across businesses.

Sessionizing Uber Trips in Real Time

Image of birds flying
Uber's many data flows required modeling the data associated with a specific task, such as a rider trip, into a state machine. The state machine lets engineers focus on just the events needed to successfully accomplish a trip.

How to Get a Better GAN (Almost) for Free: Introducing the Metropolis-Hastings GAN

Metropolis-Hastings Generative Adversarial Networks (GANs) leverage the discriminator to pick better samples from the generator after ML model training is done.

How Uber’s New Driver App Overcomes Network Lag

Carbon: Optimistic Mode article feature image
In our continuing series about building our new driver app, Uber engineers discuss building its Optimistic Mode feature, which lets the app continue functioning while traversing network lag areas.

Montezuma’s Revenge Solved by Go-Explore, a New Algorithm for Hard-Exploration Problems (Sets Records on Pitfall, Too)

Uber AI Labs introduces Go-Explore, a new reinforcement learning algorithm for solving a variety of challenging problems, especially in robotics.

Collaboration at Scale: Highlights from Uber Open Summit 2018

Uber AI Chief Scientist Zoubin Ghahramani speaks at Uber Open Summit 2018
Uber hosted its first Open Summit on November 15, inviting the open source community to learn about our open source projects from the engineers who use them every day. Check out highlights from the day, including keynotes from the Linux Foundation's Jim Zemlin and Uber AI's Zoubin Ghahramani.

Observability at Scale: Building Uber’s Alerting Ecosystem

Uber’s Observability team built a robust, scalable metrics and alerting pipeline to detect, mitigate, and notify engineers of issues as they occur.

Uber Joins the Linux Foundation as a Gold Member

Announced during the Uber Open Summit 2018, we extend our commitment to open source by joining the Linux Foundation as a Gold Member.

Experience in AI: Uber Hires Jan Pedersen

Jan Pedersen announcement feature image
Uber welcomes Jan Pedersen as a Distinguished Scientist to our Uber AI group, where he will bring his extensive experience to our efforts in improving artificial intelligence and machine learning.

NVIDIA: Accelerating Deep Learning with Uber’s Horovod

Horovod, Uber's open source distributed deep learning system, enables NVIDIA to scale model training from one to eight GPUs for their self-driving sensing and perception technologies.

Announcing the 2019 Uber AI Residency

The Uber AI Residency is a 12-month training program for academics and professionals interested in becoming an AI researcher with Uber AI Labs or Uber ATG.

My Journey from Working as a Fabric Weaver in Ethiopia to Becoming a Software Engineer at Uber in San Francisco

Samuel Zemedkun reflects on his immigrant experience and how his part-time driving through the Uber platform funded his education and inspired his decision to join the company.

Popular Articles