Job Title

About the Role Ubers Marketplace is at the heart of Ubers 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. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders. We are looking for exceptional ML engineers with a track record of extraordinary impact and 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 teams technical direction and solve some of Ubers most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide. What You Will Do Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence 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 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, or equivalent technical background with exceptional demonstrated impact 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters Proficiency in programming languages such as Python, Scala, Java, or Go Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization) Preferred Qualifications Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while 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 Proficiency 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 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 lets move the world forward, together. Offices continue to be central to collaboration and Ubers 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 . #J-18808-Ljbffr