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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.

Requirements

• Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
• Familiarity with modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization), combined with proven ability and ambition to continuously deepen expertise in these areas
• Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
• Proficiency in programming languages such as Python, Scala, Java, or Go
• 2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
• Experience in reinforcement learning and causal machine learning

Responsibilities

• 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
• Partner with senior engineers to plan the scope and execution of projects and mentor junior team members on design and implementation
• Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
• lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning.

Other

• Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
• 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
• Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office.