Maintain overall marketplace reliability by balancing supply/demand in real-time through dynamic pricing for Uber's mission to make transport accessible
Requirements
- Expertise in deep learning and optimization algorithms
- Experience with ML frameworks such as PyTorch and TensorFlow
- Experience building and productionizing innovative end-to-end Machine Learning systems
- Proficiency in one or more coding languages such as Python, Java, Go, or C++
- Experience in serving and monitoring online training systems such as real time recommendation systems
- Experience handling time series data and time series forecasting (experience handling spatial temporal data is plus)
- Experience in inference optimization and monitoring model performance efficiency and being able to identify bottlenecks
Responsibilities
- Build and train machine learning models
- Initiate new areas where machine learning models can make a large impact on the surge algorithm
- Create a safe ML deployment and observability system
Other
- PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning or Masters with 2+ years of experience
- Strong communication skills and can work effectively with cross-functional partners
- Strong sense of ownership and tenacity toward hard machine-learning projects
- Must spend at least half of work time in assigned office, unless formally approved to work fully remotely
- Eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp
