[jobs] [ML Engineering] Come build driver pricing algorithms at Uber Marketplace

[Karuna Ahuja]

We have multiple MLE roles open within Uber Marketplace in SF/South Bay offices. If interested, shoot me an email with your resume. Job details below

https://www.uber.com/global/en/careers/list/64955/

Uber's Marketplace Engineering team creates the technology behind our ridesharing marketplace by connecting riders with drivers at the push of a button. Our solutions expand user access, deliver reliability, and provide more transportation choices to users across our global markets.

About the Role

Uber's Marketplace Engineering team creates the technology behind our ridesharing marketplace by connecting riders with drivers at the push of a button. Our solutions expand user access, deliver reliability, and provide more transportation choices to users across our global markets.

About the Team

This team brings in the power of scale, reliability and automation to the Marketplace Pricing ecosystem. The team focuses on Applied Machine Learning and is responsible for scaling the state-of-the-art Machine Learning and Deep Learning models to run at Uber's global scale. The challenges range from building real-time and offline distributed data processing pipelines for Feature Engineering and Automation as well as building systems and frameworks to deploy, scale, manage and monitor Real-time ML models and more. These models power several products at Uber including Real-time Pricing and Driver Movement.

What You'll Do

• Tech lead Machine learning efforts and innovation in Pricing and Incentives.
• Lead a small cross-functional team to deliver on cross-team projects, with exceptional execution.
• Design and build ML pipelines to launch ML / DL models at Uber's global scale with world-class observability.
• Collaborate with Sr. and Staff Engineers, Product Managers and Data Scientists closely.

Basic Qualifications

• 5 Minimum Years of industry experience with a Masters or Bachelors degree in relevant fields (CS, Stats, etc.).
• 3 Minimum Year on Machine Learning, Statistics, Optimization and Data Mining.
• Led cross-functional ML teams to solve vaguely defined business problems.
• Expertise in one or more object-oriented languages, including C++, Java, Python, Go or Scala.

Preferred Qualifications

• Strong understanding of linear/convex optimization, primal-dual methods and other computational techniques, and applying it to real world problems.
• Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
• Experience working with Data Processing technologies such as Hive, Spark, Flink, etc. and ML frameworks such as SKLearn, Tensorflow, etc.