Machine Learning Engineer II, Pricing

About The Role

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. We use machine learning, optimization, and algorithmic game theory to set driver prices that dynamically align customers' and partners' interests while maximizing the value created by the marketplace.

We are looking for candidates with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.

What You Will Do

• Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
• Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
• Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
  
  

Basic Qualifications:

• Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research
• 2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
• Proficiency in programming languages such as Python, Scala, Java, or Go
• Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
• Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
• Familiarity with machine learning algorithms and mathematical optimization (e.g. LP, convex optimization)
  
  

Preferred Qualifications:

• Experience in translating ambiguous business problems into technical solutions in a structured and principled way
• Strong communication skills, including through documentation and design discussions
• Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
• Experience in reinforcement learning and causal machine learning
  
  

For Canada-based roles: The base salary range for this role is CAD$136,000 per year - CAD$151,000 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 https://www.uber.com/careers/benefits., For Canada-based roles: The base salary range for this role is CAD$136,000 per year - CAD$151,000 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 https://www.uber.com/careers/benefits.