Staff Machine Learning Engineer
Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Oct 23, 2026. Uber scores A on the Alion truth index.
About the Role
Uber Marketplace is at the heart of Uber’s business, with Rider Pricing playing a critical role by setting prices and targeting promotions for Uber riders. Our team’s mission is to drive revenue growth, ridership growth and Uber’s profitability through advanced machine learning and data science. We build reliable, scalable platforms that optimize rider pricing in both real-time and offline systems, including baseline trip pricing and targeted discounts.
The Rider Pricing team is a fast-moving, high-opportunity space where you’ll have the chance to make a significant impact on the business. On this team, your work will affect over 95% of Uber’s mobility business revenue. You’ll take ownership of one key pillar of the rider pricing domain and lead the technical direction for improving our pricing algorithms, optimization algorithms and models. You will work across ML, serving, and optimization system components, and set technical direction for modeling best practices across model building, evaluation and deployment.
In this role, you'll apply advanced machine learning technologies, including deep learning, generative AI for causal modeling, representation learning and personalization, to optimize Uber’s pricing. You will also work with serving infrastructure and product teams to design and evolve the rider pricing systems to support new product and algorithm evolutions and drive Uber’s top-line rider and revenue growth.
What You’ll Do
- Lead a group of SWEs and MLEs working on Uber’s rider pricing to develop and implement new machine learning and optimization techniques powering billions of rides around the world, and helping riders achieve their mobility needs.
- Improve the performance of models and algorithms powering pricing algorithms and promotion targeting.
- Own the problem E2E, including working with cross-functional teams to define the product and/or technical roadmap.
- Mentor more junior team members by role modeling ML best practices. Collaborate with cross-functional teams to ensure alignment and drive Uber’s ridership and revenue growth. Help Uber’s end-users by making mobility options accessible and affordable.
Basic Qualifications
- Masters degree in Computer Science, Engineering, Mathematics, or a related field, with 7+ years of full-time engineering experience.
- Proficiency in one or more programming languages (e.g., C, C++, Java, Python, Go).
- Experience with machine learning and optimization algorithms.
Preferred Qualifications
- PhD in Computer Science, Engineering, Mathematics, or a related field, with 2+ years of full-time engineering experience.
- Experience solving complex business problems by translating them into machine learning and optimization solutions.
- Familiarity with large-scale data systems (e.g., Spark, Hive) and experience building production-ready algorithmic systems.
- Strong background in deep learning, generative AI, causal modeling, and reinforcement learning.
For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.