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Tag: Uber Eats

Year in Review: 2019 Highlights from the Uber Engineering Blog

To cap off 2019, the Uber Engineering Blog editors present a selection of our most popular articles covering a range of technical topics, from AI to mobile development.

Uber Infrastructure in 2019: Improving Reliability, Driving Customer Satisfaction

In 2019, Uber's Infrastructure team built new services and systems to enable resource savings, efficiency gains, and greater resilience across our technology stack.

Food Discovery with Uber Eats: Using Graph Learning to Power Recommendations

By integrating graph learning techniques with our Uber Eats recommendation system, we created a more seamless and individualized user experience for eaters on our platform.

Introducing Menu Maker: Uber Eats’ New Menu Management Tool

To simplify the Uber Eats experience for our restaurant-partners, we built Menu Maker, a web-based tool for seamlessly managing menus on the Uber Eats app.
Conducting Better Business with Uber's Open Source Orchestration Tool, Cadence

Conducting Better Business with Uber’s Open Source Orchestration Tool, Cadence

Uber engineers describe Cadence, Uber’s open source workflow orchestration tool, its architecture, and its use in a series of informative presentations.

Using Causal Inference to Improve the Uber User Experience

Uber Labs leverages causal inference, a statistical method for better understanding the cause of experiment results, to improve our products and operations analysis.

Mitigating Risk in a Three-Sided Marketplace: A Conversation with Trupti Natu and Neel Mouleeswaran...

We sat down with a risk strategy manager and a risk engineer to discuss how they build solutions to minimize risk in the Uber Eats three-sided marketplace.

Building Locally, Scaling Globally: Meet the Tech Team at Uber New York City

Ever wondered what it’s like to work in tech at Uber New York City? Just blocks from Times Square and Bryant Park, Uber’s new office in midtown Manhattan is home to more than a dozen teams, hundreds of employees (and growing), and a wide variety of engineering roles.

Women in Data Science at Uber: Moving the World With Data

During an October 2018 meetup, members of our Women in Statistics, Data, Optimization, and Machine Learning (WiSDOM) group presented on their technical work at Uber.

Year in Review: 2018 Highlights from the Uber Engineering Blog

Our editors spotlight some of the year's most popular articles, from an overview of our Big Data platform to a first-person account of an engineer's immigrant journey.

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.
Scaling Cash Payments in Uber Eats - feature_image

Scaling Cash Payments in Uber Eats

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.

Scaling Machine Learning at Uber with Michelangelo

Uber built Michelangelo, our machine learning platform, in 2015. Three years later, we reflect our journey to scaling ML at Uber and lessons learned along the way.

From Financial Models to iOS Model View Controllers: Making a Career Move to Programming

Joe Zhou, the 7th iOS engineer on the Uber Eats team, offers advice for those considering taking the plunge into programming.
Food Discovery with Uber Eats: Recommending for the Marketplace

Food Discovery with Uber Eats: Recommending for the Marketplace

Uber Eats engineers describe how they surface restaurant recommendations in the app using multi-objective optimization to give eaters the most satisfying experience while maintaining the health of the Uber Eats marketplace.

Under the Hood of Uber’s Experimentation Platform

Uber's experimentation platform empowers us to improve the customer experience by allowing teams to launch, debug, measure, and monitor product changes.

Seeing Double: Meet Uber’s Identical Twin Data Scientists

Afshine and Shervine Amidi, identical twins, discuss their journeys to data science and how their work at Uber helps teams improve user experiences on our platform.
How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats

How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats

Using GPS and sensor data from Android phones, Uber engineers develop a state model for trips taken by Uber Eats delivery-partners, helping to optimize trip timing for delivery-partners and eaters alike.
Query understanding article feature image

Food Discovery with Uber Eats: Building a Query Understanding Engine

Uber engineers share how we process search terms for our Uber Eats service, using query understanding and expansion to find restaurants and menu items that best match what our eaters want.
Benito Sanchez at work

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.

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