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16 MAY

Engineering a Job-based Forecasting Workflow for Observability Anomaly Detection

Uber’s Observability Applications team overhauled our anomaly detection platform’s workflow to enable the intuitive and performant backfilling of forecasts, paving the way for more intelligent alerting.

10 MAY

Customer-focused Engineering at Uber: A Q&A with Jörg Heilig, VP of Ridesharing and Eats Engineering

In this interview, Uber Vice President of Engineering for Ridesharing and Eats Jörg Heilig talks about taking a leadership role in a large engineering organization with a broad portfolio and the priorities being set for 2018.

7 MAY

Thank You for Your Feedback: Improving the Uber Engineering Workflow with uRate

uRate empowers both Uber employees and customers to provide quick and efficient feedback on tools and products, enabling engineers to build more responsive services.

4 MAY

Uncovering Genius: Zach Singleton on Preparing Black Male CS Students for Tech Careers

Product Manager Zach Singleton talks about how Uber partnered with The Hidden Genius Project to create the Career Prep Program, a one-year course that prepares black male computer science students for careers in tech.

30 APR

Introducing Nanoscope: An Extremely Accurate Method Tracing Tool for Android

Uber's Mobile Engineering team open sources Nanoscope, a new method tracing tool for Android that enables developers to more accurately debug difficult performance issues.

26 APR

Measuring the Intrinsic Dimension of Objective Landscapes

Curious about what it is like to traverse the high-dimensional loss landscapes of modern neural networks? Check out Uber AI Labs’ latest research on measuring intrinsic dimension to find out.

23 APR

Accelerating Deep Neuroevolution: Train Atari in Hours on a Single Personal Computer

Applying hardware acceleration to deep neuroevolution in what is now an open source project, Uber AI Labs was able to train a neural network to play Atari in just a few hours on a single personal computer, making this type of research accessible to a far greater number of people.

19 APR

Rethinking GPS: Engineering Next-Gen Location at Uber

Uber’s Sensing, Inference, and Research team released a software upgrade for GPS on Android phones that significantly improves location accuracy in urban environments.

18 APR

Mediation Modeling at Uber: Understanding Why Product Changes Work (and Don’t Work)

Uber Labs leverages mediation modeling to better understand the relationship between product updates and their outcomes, leading to improved customer experiences on our platform.

12 APR

Scaling for Growth: A Q&A with Uber’s VP of Core Infrastructure, Matthew Mengerink

Matthew Mengerink, Vice President of Engineering for Uber’s Core Infrastructure group, talks about how converging technologies and cloud computing contribute to stable and scalable growth.

10 APR

Differentiable Plasticity: A New Method for Learning to Learn

Differentiable Plasticity is a new machine learning method for training neural networks to change their connection weights adaptively even after training is completed, allowing a form of learning inspired by the lifelong plasticity of biological brains.

5 APR

Scaling Uber’s Hadoop Distributed File System for Growth

Uber's Data Infrastructure team overhauled our approach to scaling our storage infrastructure by incorporating several new features and functionalities, including ViewFs, NameNode garbage collection tuning, and an HDFS load management service.

3 APR

Fighting Resistance, Finding Balance: A Conversation with Sophia Vicent, Uber’s Director of Technical Program Management

Sophia Vicent joined Uber after spending 10 years away from the workforce to raise her daughter. We caught up with her to discuss her journey in technical program management.

28 MAR

Building Check-In Queuing & Appointment Scheduling for In-Person Support at Uber

Uber's Customer Obsession Engineering team developed new check-in queuing and appointment systems to improve the customer experience for driver-partners at our Greenlight Hubs.

26 MAR

Open Source at Uber: A Conversation with Nicolas Garcia Belmonte, Head of Visualization

Nicolas Garcia Belmonte, head of visualization, talks about his experience getting started in open source and the role it plays in his work at Uber.

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.

9 MAR

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.

7 MAR

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.

1 MAR

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.

9 FEB

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.

6 FEB

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.