Uber Staff Machine Learning Engineer - Dynamic Pricing 

United States, West Virginia 

55191516

What You'll Do

You will work with a mixed team of Engineers, Operations Researchers, and Economists to build large-scale pricing optimization systems to set prices based on real-time marketplace conditions for Uber’s rides products globally.

• Build and train machine learning models.
• Initiate new areas where machine learning models can make a large impact on the o

Basic Qualifications

• PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning.
• 4+ years of experience in an ML role with an emphasis on data and experiment driven model development.
• 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++.
• Strong communication skills and can work effectively with cross-functional partners.
• Strong sense of ownership and tenacity toward hard machine-learning projects.

Preferred Qualifications

• Experience in serving and monitoring online training systems such as real time recommendation systems.
• Experience designing and implementing novel metrics for performance evaluation.
• Experience handling time series data and time series forecasting (experience handling spatial temporal data is plus).
• Deep understanding of models such as VAE (Variational Auto Encoder), SSM (State space model), and Normalizing Flow.
• Experience in inference optimization and monitoring model performance efficiency and being able to identify bottlenecks.
• Proven track record in conducting experiments and tracking models in high-complexity environments.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link .