Uber's marketplace team is looking to optimize incentive allocation and dynamic trip pricing to balance the market and maximize revenue.
Requirements
- 4+ years full-time Machine Learning Engineering work experience in leveraging machine learning/statistics/optimization to build models in production
- 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
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.
Other
- PhD or equivalent in Computer Science, Engineering, Mathematics or related field
- Collaborative and work well with, and contribute to, a team
