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 experienced 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.
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What You Will Do:
- Lead the design, development, and productionization of 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
- Partner with the marketplace leadership team to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers
- 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
- 6+ 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
- Deep understanding of machine learning algorithms and mathematical optimization (e.g. LP, convex optimization)
Preferred Qualifications:
- Experience leading large complex technical projects and substantially influencing the scope and output of others
- Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
- Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
- 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$189,000 per year - CAD$210,000 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.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.