About the job
The role will be within the pricing and incentives domain in Uber's marketplace team. The team charter spans incentive allocation and optimization to balance the market and optimize revenue, dynamic trip pricing based on marketplace conditions. The role will provide an opportunity to work on some of the most strategic marketplace problems at Uber scale that impact Uber's global business very directly.
Responsibilities
Work with product, data science, and eng leadership to shape the technical roadmap and problem formulations for the team.
Leverage algorithmic knowledge in machine learning/optimization/statistics to design robust engineering solutions to positively impact Uber's business.
Shape the MLE role and uplevel MLE talents in the org.
Be responsible for the End to End of the product - ML model pipeline & system design, implementation, AB testing, and rollout. Work with the team to productionize the solutions at scale.
Qualifications
Minimum
PhD or equivalent in Computer Science, Engineering, Mathematics or related field
4+ years full-time Machine Learning Engineering work experience in leveraging machine learning/statistics/optimization to build models in production
Collaborative and work well with, and contribute to, a team
Preferred
Experience building algorithms with large scale data
Track record of building large-scale, highly-available systems for both batch and streaming
Deep domain expertise and are one of the recognized specialists in one or multiple areas like reinforcement learning, personalization, or deep learning.
Experience in combining observational data with experimental data for building causal models.
Experience working on large scale Machine Learning platforms