The business problem is to build and maintain services that generate millions of incentives for gig work earners on the Uber platform, ensuring adequate supply to meet market demands across time and space.
Requirements
- Comfortable programming in at least one major language such as Python (preferred), Scala, Go,...
- Experience with any of the following: Spark, Hive, Kafka, Cassandra.
- Experience building and productizing innovative end-to-end Machine Learning systems.
- Experience writing custom models in Pytorch or Tensorflow/Keras.
- Experience in the design and development of ML pipelines and workflows.
- Experience building backend services using any mainstream languages like C/C++/Java/Go
- Experience collaborating cross-functionally with product and other engineering roles.
Responsibilities
- Solve ambitious, challenging business problems using data-driven approaches.
- Build and optimize models and algorithms powering Earner incentive levers across the Uber marketplace.
- Improve the overall model lifecycle for the team by building solutions around model observability, performance tuning and tracking.
- Own the problem E2E, including working with cross-functional teams to define the product and/or technical roadmap.
- Mentor more junior team members by role modeling ML best practices.
- Collaborate with cross-functional teams to ensure alignment and drive Uber’s ridership and revenue growth.
- Help Uber’s end-users by making mobility options accessible and affordable.
Other
- Masters Degree or equivalent experience in field of Computer Science or Machine Learning.
- 3 years minimum of industry experience as a Machine Learning Engineer
- Driven and curious.
- Exceptional technical communication skills.
- For New York, NY-based roles, employees are expected to spend at least half of their work time in their assigned office.
