Software Engineer - Full Stack

San Francisco, CA, United States

As a Full-Stack Engineer at Uber, you’ll be working on code from the deepest levels of our stack to very top. You’ll be working on creating dynamic pixel-perfect web UIs while simultaneously solving scalability problems and scaling complex business logic. Your work will impact live riders, eaters, driver-partners, and operations teams across the globe. Our teams span from the traditional ridesharing business to the new emerging products around UberEATS, our own Mapping technology, and Self-Driving cars.

You will build user-facing products, handle and store thousands of payment transactions per second, and develop intelligent fraud prevention strategies that scale. From building maps that help move millions of people, to the messaging systems that let us interact with them - the work you do will impact every single Uber request.

About you

  • Expertise in one or more object oriented programming language (e.g. Python, Go, Java, C++) as well as skills in Javascript and the web.
  • Experience with developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
  • Experience with large-scale distributed storage and database systems (SQL or NoSQL, e.g. MySQL, Cassandra)
  • Ability to decompose complex business problems and lead a team in solving them

Bonus points if

  • BS/MS/PhD in Computer Science or a related field
  • We love React - so knowledge there is a plus.

Team-specific focus areas

Additionally, Uber has a variety of roles and teams for you depending on where your interests match best.

  • High performance systems - Experience with building high performance distributed systems that can scale to 100,000s QPS.
  • Core Infrastructure - Experience with developing and running large scale distributed storage systems, service oriented architectures, and reliable monitoring and deployment infrastructure.
  • Data Processing - experience with building and maintaining large scale and/or real-time complex data processing pipelines using Kafka, Hadoop, Hive, Storm, and Zookeeper
  • Machine Learning - experience with machine learning, information retrieval, algorithmic complexity, data mining, pricing, optimization.
  • Geospatial - Familiarity with geospatial datasets and services, such as maps, local search, points of interest and business listings data, mobile device location and GPS traces.
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