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Senior Software Engineer (ML or BE) - Marketplace

Machine Learning, Engineering
in Toronto, Canada

About the Role

The Earner Incentives team is looking for both backend and machine learning engineers.The team's charter is to design, develop, build and maintain software products to efficiently incentivize earners to maximize Uber's growth and help maintain marketplace balance. The role provides an opportunity to work on highly impactful and strategic marketplace problems at Uber's scale that are critical to Uber's success globally.

The team builds and maintains a highly scalable offer generation and execution platform, machine learning and data pipelines and incentive user interfaces that incentivize earners to drive on Uber platform and support Uber's growth efficiently. The key challenges for the role include building and operating highly scalable high QPS systems to generate and execute offers, build feature engineering and modeling pipelines, improving models to improve prediction accuracy, implementing new algorithms to improve incentive efficiency as well as building highly comprehensible and easy to use user interfaces.

What You'll Do

  • Design, implement and maintain systems, APIs for offer generation, incentive state management and incentive user experience
  • Design, implement and iterate on ML models and ML based systems
  • Design, Build and Implement model training and feature engineering pipelines
  • Work cross functionally with adjacent engineering teams to deliver best in breed experience to Drivers.
  • Collaborate closely with Product Managers, Prod Ops, Central Operations teams and have an opportunity to craft the future of driver incentives at Uber.

What You'll Need

  • Bachelor's degree in Computer Science or related technical field or equivalent practical experience
  • At least two (2) years of software engineering experience
  • Experience coding with Go, C++, Java or Python.

Bonus Points If:

  • Experience building microservices and APIs
  • Proven experience of shipping high-quality features on schedule
  • Experience with Hive or Spark
  • Experience with Machine Learning
  • Experience working with Data Processing technologies such as Hive, Spark, Flink, etc. and ML frameworks such as SKLearn, Tensorflow, etc.
  • Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
  • Experience with experimentation and ability to interpret the results and iterate.
  • Good understanding of linear/convex optimization and applying it to real world problems

About The Team

The Earner Incentives team builds the platform for generating efficient incentives for drivers, measuring progress of drivers towards achieving those incentives and then paying once incentive goals are achieved. It plays a meaningful role in ensuring adequate supply to meet the market demands across time and space. We are responsible for the algorithms to generate the incentive offers, state machine to track drivers progress towards completing incentives & paying them out and providing excellent incentive experience to drivers, so they are provided with easy to understand information about incentives, their progress and payouts. There is an excellent growth opportunity for talented engineers as it is a very high impact role that is central to our success in the marketplace.

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.


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Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran Status, or any other characteristic protected by law.