We’re changing the way people think about transportation. Not that long ago we were just an app to request premium black cars in a few metropolitan areas. Now we’re a part of the logistical fabric of more than 600 cities around the world. Whether it’s a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.
For the people who drive with Uber, our app represents a flexible new way to earn money. For cities, we help strengthen local economies, improve access to transportation, and make streets safer.
And that’s just what we’re doing today. We’re thinking about the future, too. With teams working on autonomous trucking and self-driving cars, we’re in for the long haul. We’re reimagining how people and things move from one place to the next.
About The Role
We are looking for experienced Software Engineers to join our Deep Learning Infrastructure Engineering team. This group is perfect for those engineers looking to tackle the types of deep learning at scale / distributed systems programming challenges that are critical to Uber’s continued success.
What You’ll Do
What You’ll Need
About The Team
The Machine Learning Platform team builds the end-to-end systems and tools to enable teams around Uber to build and deploy machine learning solutions at scale. The platform is used by more than a dozen teams around Uber, including EATs, Map Services, Fraud, Marketplace, Finance, and ATG (autonomous cars).
The Deep Learning Infrastructure Engineering team is composed of experts in deep learning, data-structures / algorithms, distributed systems, and system performance and analysis. We need people with a solid computer science background who love putting their ideas into working code.
This is some of the most leveraged work in the company. The systems that we build get used across the multitude of Uber deep learning based services and deployments. The software that we write needs to be horizontally scalable, fault-tolerant, well monitored, and easy to debug.