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22 MAR

Introducing QALM, Uber’s QoS Load Management Framework

Uber Engineering built QALM, a smart load management tool allowing for graceful degradation by preserving critical system requests and shedding non-critical requests.

16 MAR

VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution

Uber AI Labs introduces Visual Inspector for Neuroevolution (VINE), an open source interactive data visualization tool to help neuroevolution researchers better understand this family of algorithms.

15 MAR

Out of the Arcade: Designing the Uber Kiosk

The design of Uber's driver support kiosk drew inspiration from arcade games of the past along with new thinking on how to engage with customers in public spaces.

13 MAR

Scaling Infrastructure Management with Grail

Uber Engineering built Grail, our infrastructure management platform, to aggregate the current state of our systems into a single global view, spanning all zones and regions.


From Milking Cows to Writing Code: A Dreamer’s Journey

Brought to the US when he was 10 years old, DACA gave Benito Sanchez the security to go to college and get a job in technology.


Celebrating Uber Bangalore’s Women in Tech

In honor of International Women’s Day (March 8), Disha Pancholi, Uber Bangalore Engineering’s Site Program Manager, sat down with members of her office to discuss their experiences as women in technology.


Queryparser, an Open Source Tool for Parsing and Analyzing SQL

Written in Haskell, Queryparser is Uber Engineering's open source tool for parsing and analyzing SQL queries that makes it easy to identify foreign-key relationships in large data warehouses.

28 FEB

Scalable Systems & Scalable Careers: A Chat with Uber’s Sumbry

What do Site Reliability Engineering (SRE) and mentorship have in common? According to Uber SRE manager Sumbry, both areas focus on growth.

22 FEB

Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore

Migrating our Schemaless sharding layer from Python to Go while in production demonstrated that it was possible for us to rewrite the frontend of a massive datastore with zero downtime.

20 FEB

Introducing the Uber AI Residency

Interested in accelerating your career by tackling some of Uber’s most challenging AI problems? Apply for the Uber AI Residency, a research fellowship dedicated to fostering the next generation of AI talent.

16 FEB

Building Reliable Reprocessing and Dead Letter Queues with Kafka

The Uber Insurance Engineering team extended Kafka’s role in our existing event-driven architecture by using non-blocking request reprocessing and dead letter queues (DLQ) to achieve decoupled, observable error-handling without disrupting real-time traffic.

14 FEB

Implementing Model-Agnosticism in Uber’s Real-Time Anomaly Detection Platform

Uber Engineering extended our anomaly detection platform's ability to integrate new forecast models, allowing this critical on-call service to scale to meet more complex use cases.


Designing Uber’s Product Manager Bootcamp

Uber’s Product Manager Bootcamp facilitates a more robust and streamlined onboarding experience for new PMs, leading to increased alignment, communication, and collaboration between product teams.


Meet Uber’s Software Engineer Apprentices

Uber's Software Engineer Apprentice Program gives developers with non-traditional paths to programming an opportunity to work on industry-level software while receiving extended training and mentorship.

31 JAN

NEAL, Uber’s Open Source Language-Agnostic Linting Platform

Not Exactly a Linter (NEAL) takes code reviews one step closer to full automation by allowing engineers to write custom syntax-based rules in any language.

24 JAN

Omphalos, Uber’s Parallel and Language-Extensible Time Series Backtesting Tool

Uber Engineering created Omphalos, our new backtesting framework, to enable efficient and reliable comparison of forecasting models across languages.

19 JAN

Playing the Perfect Game: Building Uber Eats on Android

To mark the two-year anniversary of Uber Eats, Android engineer Hilary Karls discusses how her team's commitment to "playing the perfect game" resulted in one of Uber’s most successful products.

16 JAN

SBNet: Leveraging Activation Block Sparsity for Speeding up Convolutional Neural Networks

Uber ATG Toronto developed Sparse Blocks Network (SBNet), an open source algorithm for TensorFlow, to speed up inference of our 3D vehicle detection systems while lowering computational costs.

11 JAN

Harnessing Code Generation to Increase Reliability & Productivity on iOS at Uber

Uber's mobile engineers leverage code generation to make our applications more reliable and boost developer productivity.


Engineering Confidence: A Beginner’s Guide to Overcoming Imposter Syndrome

How do you overcome imposter syndrome? Act with confidence, follow your first instinct, and always be learning and teaching.


COTA: Improving Uber Customer Care with NLP & Machine Learning

In this article, Uber Engineering introduces our Customer Obsession Ticket Assistant (COTA), a new tool that puts machine learning and natural language processing models in the service of customer care to help agents deliver improved support experiences.

27 DEC

Architects of Infrastructure: Meet Uber Aarhus Engineering

Get to know Uber Aarhus Engineering and the work they do behind the scenes to build and maintain our storage and compute platforms.

22 DEC

Year in Review: 2017 Highlights from Uber Open Source

As we approach the New Year, Uber Open Source revisits some of Uber Engineering's most popular projects from 2017.

21 DEC

Year in Review: 2017 Highlights from the Uber Engineering Blog

To ring in the New Year, the Uber Engineering Blog shares some of our editor's picks for 2017.

18 DEC

Welcoming the Era of Deep Neuroevolution

By leveraging neuroevolution to train deep neural networks, Uber AI Labs is developing solutions to solve reinforcement learning problems.

14 DEC

Unifying Mobile Onboarding Experiences at Uber

By unifying mobile onboarding experiences for our new rider app, Uber Engineering made it easier than ever before for users to "get moving."

12 DEC

Navigating the Engineering Interview Process at Uber & Beyond

Up for the challenge of developing at unprecedented scale? First, learn what it takes to master the technical interview process at Uber.


Gleaning Insights from Uber’s Partner Activity Matrix with Genomic Biclustering and Machine Learning

Uber Engineering's partner activity matrix leverages biclustering and machine learning to better understand the diversity of user experiences on our driver app.

30 NOV

Reliability at Scale: Engineering an Uneventful New Year’s Eve

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.