Senior Machine Learning Engineer - Marketplace Earner Incentives - #450810
Uber
Date: 6 hours ago
City: Toronto, ON
Contract type: Full time

About The Role
Earner Incentives is one of the fastest-growing products at Uber. As an Engineer on the Earner Incentives team you will be responsible to build and maintain services that generate millions of incentives for gig work earners on the Uber platform.
Incentives Platform is used 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 critical role in ensuring adequate supply to meet the market demands across time and space. The combination of technical challenges and cross functional work will allow you to harness you ML skills in multiple dimensions.
The Earner Incentives team is a fast-moving, high-opportunity space where you'll have the chance to make a significant impact on the business. You'll take ownership of one key pillar of the promotions or incentive domain and lead the technical direction for improving our core algorithms, optimization across different type of incentives algorithms and models. The role offers a close collaboration with the Platform backend team and Uber ML infra so you will also have opportunity to contribute to scaling model infrastructure for the team. You work will cut across ML, serving, and optimization system components, and help set technical direction for modeling best practices across model building, evaluation and deployment.
Join us to work on some of the most exciting challenges on this journey. ---- Basic Qualifications ---- ---- Preferred Qualifications ----
Earner Incentives is one of the fastest-growing products at Uber. As an Engineer on the Earner Incentives team you will be responsible to build and maintain services that generate millions of incentives for gig work earners on the Uber platform.
Incentives Platform is used 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 critical role in ensuring adequate supply to meet the market demands across time and space. The combination of technical challenges and cross functional work will allow you to harness you ML skills in multiple dimensions.
The Earner Incentives team is a fast-moving, high-opportunity space where you'll have the chance to make a significant impact on the business. You'll take ownership of one key pillar of the promotions or incentive domain and lead the technical direction for improving our core algorithms, optimization across different type of incentives algorithms and models. The role offers a close collaboration with the Platform backend team and Uber ML infra so you will also have opportunity to contribute to scaling model infrastructure for the team. You work will cut across ML, serving, and optimization system components, and help set technical direction for modeling best practices across model building, evaluation and deployment.
Join us to work on some of the most exciting challenges on this journey. ---- Basic Qualifications ---- ---- Preferred Qualifications ----
- What You Will Do ----
- Solve ambituous, 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.
- Masters Degree or equivalent experience in field of Computer Science or Machine Learning.
- 3 years minimum of industry experience as a Machine Learning Engineer
- Comfortable programming in at least one major language such as Python (preferred), Scala, Go,...
- Experience collaborating cross-functionally with product and other engineering roles.
- Experience with any of the following: Spark, Hive, Kafka, Cassandra.
- Experience building and productizing innovative end-to-end Machine Learning systems.
- Driven and curious.
- Exceptional technical communication skills.
- 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
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