Principal Engineer

Are you passionate about shaping business and product strategy through the power of data? Principal engineers at Uber have a deep impact across a wide variety of business and technology decisions spanning multiple programs, projects and locations. They are humble teachers, technically mentoring a team of passionate engineers while also delivering uniquely challenging projects. A Principal-level Engineering role at Uber is special, representing the top 2% of Engineers at Uber.
The Marketplace Engineering team is looking for an exceptional Principal Engineer to lead breakthrough ML innovation in Ubers Driver Pricing organization. This is a high-impact role where youll architect and build next-generation ML systems that directly optimize marketplace efficiency and driver earnings for millions of drivers globally.
Youll tackle some of the most complex problems in applied machine learning: real-time pricing optimization, supply-demand balancing, and driver behavior modeling at unprecedented scale. Your work will involve cutting-edge techniques including causal inference, reinforcement learning, algorithmic game theory, and multi-objective optimization to solve challenges that dont exist anywhere else in the industry.
As a Principal Engineer reporting directly to the Engineering Director, youll drive technical strategy, mentor senior engineers, and establish ML engineering excellence across the Driver Pricing organization while solving problems that directly impact tens of billions of dollars in marketplace transactions.
Lead the design and implementation of advanced ML systems for dynamic pricing algorithms serving millions of drivers across 70+ countries around the world
Drive breakthrough research in causal ML, reinforcement learning, algorithmic game theory, and multi-objective optimization for marketplace optimization with strategic agents
Own end-to-end ML model lifecycle from research through production deployment and continuous optimization
Develop and enforce best practices in system design, ensuring data integrity, security, and optimal performance
Serve as a representative for the Marketplace organization to the broader internal and external technical community
Contribute to the eng brand for Marketplace and serve as a talent magnet to help attract and retain talent for the team
Stay abreast of industry trends and emerging technologies in software engineering, focused particularly on ML/AI, to enhance our systems and processes continually
Platform & Architecture
Build scalable ML architecture and feature management systems supporting Driver Pricing and broader Marketplace teams
Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies
Establish ML engineering best practices, monitoring, and operational excellence across the organization
Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms
Partner with Product, Operations, and Earner Experience teams to translate complex business requirements into ML solutions
Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research
Work with Platform Engineering teams to ensure ML systems meet reliability and performance standards
Mentor and grow senior ML engineers, establishing technical standards and engineering culture
Drive knowledge sharing and technical excellence across the Driver Pricing engineering organization
PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Masters degree with 12+ years of industry experience
~10+ years of experience building and deploying ML models in large-scale production environments
~ Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch, JAX) and distributed computing platforms (Spark, Ray)
~ Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, Algorithmic Game Theory, and Large-scale Ads Ranking/Auction Systems
~ Proven track record of leading complex ML projects from research through production with significant measurable business impact
~ Strong programming skills in Python, Java, or Go with experience building production ML systems
~ Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second)
~ Advanced Deep Learning and Neural Network architectures
~ Scalable ML architecture and distributed model training
~ Feature engineering and real-time feature serving
~ ML model deployment, monitoring, and lifecycle management
~ Statistical analysis and experimental design for ML systems
~ Algorithmic Game Theory for strategic agent modeling

Bonus Points If
Marketplace or two-sided platform ML experience with understanding of supply-demand dynamics and pricing mechanisms
Experience with causal inference methodologies and their application to business problems with network effects
Experience with real-time ML systems requiring low-latency inference and high-throughput model serving
Background in economics, operations research, or related quantitative disciplines with application to marketplace problems
Graph-based ML for network effects modeling
Driver earnings optimization affecting millions of drivers livelihoods globally
Business performance influencing tens of billions of dollars in gross bookings annually
Technical excellence establishing ML engineering standards used across Uber
Exceptional technical depth combined with practical engineering skills to deliver production ML systems
Collaborative leadership building consensus around technical decisions across multiple teams
Results orientation with focus on measurable business impact and engineering excellence
The Uber Marketplace is designed to move riders & drivers efficiently from where they are to where they want to go. Every dollar that is transacted in the Uber Marketplace (driver forecasting, dynamic pricing fares, matching driver/rider pricing, and overall marketplace health) is informed and influenced by data and our Data Science team understands, analyzes, and helps design the algorithms that enable millions of earners and consumers to ride, deliver, eat, and move daily.
The Marketplace Science & Engineering team applies their expertise in statistical modeling, machine learning, eco]]