Base Salary
$232k - $258k/yr
Responsibilities
- Set technical direction and own major charters for real-time matching optimization and ML systems.
- Design matching objectives and decision policies balancing marketplace goals across riders, drivers, and Uber.
- Develop and productionize ML-based decision systems for complex sequential and multi-agent environments.
- Apply reinforcement learning, probabilistic modeling, deep learning, causal inference, sequential decision-making, model predictive control, and feedback-control approaches.
- Build behavioral models and optimization systems that account for rider and driver responses to marketplace decisions.
- Develop simulation, experimentation, and causal measurement frameworks to evaluate policies and long-term system effects.
- Lead ambiguous 0→1 technical efforts from formulation and modeling through production inference and system integration.
- Collaborate with engineering, applied science, economics, product, and operations teams on scalable technical solutions.
- Mentor senior engineers and raise the technical bar for ML and optimization across the matching organization.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Engineering, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience.
- At least 8 years of industry experience in machine learning, or at least 6 years with a PhD or equivalent demonstrated technical depth.
- Significant experience building large-scale production ML systems, including online inference.
- Deep expertise in modern machine learning, including deep learning, reinforcement learning, and decision-making under uncertainty.
- Ability to formulate ambiguous business or system problems as tractable ML or decision problems and take them from concept to production.
- Strong backend programming and systems skills, with the ability to personally design and implement production-quality ML and optimization systems.
- Experience leading technically complex cross-functional initiatives and influencing engineering or scientific direction beyond an individual project.
- Preferred: PhD in Machine Learning, Reinforcement Learning, Control, Optimization, Robotics, Operations Research, Statistics, or a related field.
- Preferred: Deep experience with reinforcement learning, optimal control, or sequential decision-making methods.
- Preferred: Experience with marketplace optimization, robotics/autonomy, ads optimization, ranking, recommendation systems, multi-objective or multi-agent decision systems, causal inference, online or offline policy evaluation, and large-scale simulation environments.
- Preferred: Track record of introducing novel modeling or algorithmic approaches that materially improved a production system.
Benefits
- Full-time employees are eligible to participate in a 401(k) plan.
- Employees are eligible for various benefits.
- US employees may participate in Uber’s bonus program and may be offered equity awards and other compensation types.
Categories
About Uber
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.