Senior Staff Machine Learning Engineer - Marketplace Matching & Driver Pricing

This is a key role as a thought leader and key contributor to Machine Learning efforts across several key domains in Marketplace - Job-Driver Matching system, Driver offer pricing, and Driver Surge pricing. The ML models in these domains vary from causal ML models, reinforcement learning models, and forecast models. Some of the challenges in these domains is dealing with data sparsity and delay in realizing the impact of actions given the physical nature of Uber business, network effects given the drivers are a limited supply that are shared across riders, long term behavioral changes in driver community and geo differences in driver values and Uber business - all of these considerations make this problem space a challenging and open problem in ML field. The impact of this role is extremely high given the impact of the marketplace levers it supports.

The org includes Driver offer pricing, Matching, and Driver surge teams within the Uber Marketplace organization. The team owns systems that make optimum decisions on driver pricing and job-driver matching, working cross functionally with various organizations at Uber across Earner and Rider teams, Operations, and Platforms.

This role requires deep expertise in Machine Learning, including Deep Learning, Scalable ML architecture, and Feature management. Preferred skills include Causal ML, Reinforcement learning, Contextual bandit models, and Personalization and ranking experience. The ideal candidate will have a PhD or equivalent in Computer Science, Engineering, Mathematics or related field with 6 years of full-time Software Engineering work experience, or 10 years of full-time Software Engineering work experience, including 6 years of specialized experience in areas such as programming languages, large-scale training, modern machine learning algorithms, and Machine Learning Software.