On the Rides Engineering team, we write code that ignites opportunities for millions of people every day. We're focused on making Uber's core ridesharing products faster, safer, and more reliable by building scalable software solutions for riders and drivers on our platform.
About the Role
Sr Staff Engineers at Uber are expected to have a deep impact on a wide variety of technology decisions, spanning many projects across an entire org, and in many cases multiple orgs. We are looking for a technologist who has experience building consumer products at scale.
This is a unique opportunity for a seasoned engineer and strong collaborator who can work with talented people in product, design, data science, operations, and engineering to help build our next-generation consumer experience products. It's a very high impact role where you will interface with all major product & platform teams at Uber. The role requires a person whose communication and leadership is as strong as their technical chops, and who enjoys both building solutions themselves and guiding others equally passionately.
What You'll Do

• Work with product, data science, and eng leadership to shape the technical roadmap and problem formulations for the team.
• Leverage algorithmic knowledge in machine learning/optimization/statistics to design robust approaches engineering solutions to positively impact Uber's business.
• Work with the team to productionize the solutions at scale.

Basic Qualifications

• BS/BE degree in Computer Science and related field
• 7+ years of experience designing and implementing large scale distributed systems

Preferred Qualifications

• Master's in a relevant field (computer science, engineering, statistics, ML) or PhD
• Experience in leveraging machine learning/statistics/optimization to build models in production
• Some experience in leading teams either as a tech lead or a manager
• Experience building algorithms with large scale data
• Track record of building large-scale, highly-available systems for both batch and streaming
• Deep domain expertise and are one of the recognized specialists in one or multiple areas like reinforcement learning, personalization, or deep learning.