Graduate 2026 PhD Software Engineer II (Consumer Structural Pricing), United States
Role summary
Uber is seeking PhD graduates or recent PhDs in quantitative fields for a Software Engineer II role focused on Consumer Structural Pricing. This position involves working across the full lifecycle of machine learning for Uber's Delivery products, from model development and data pipelines to real-time services and user experience. The role offers the opportunity to tackle complex problems at scale, influence core pricing strategies, and drive significant impact on consumer-facing products. The team collaborates with various engineering and data science groups to build scalable systems for millions of users globally.
We're looking for machine learning engineers who are currently completing or recently completed a PhD program and who are passionate about building high-impact, consumer-facing products. In this role, you'll work across the full end-to-end flow of Uber's Delivery products-from building machine learning models and offline data pipelines, to developing real-time services, online model serving, and product user experiences. You'll have the opportunity to tackle challenging problems at scale, shape core pricing mechanisms, and drive impactful outcomes across the entire consumer journey.
About the Team
The Consumer Structural Pricing team plays a pivotal role in shaping consumer demand across Uber's Delivery business-including food delivery, groceries, and more. We work closely with other Uber Marketplace teams to build innovative products and scalable systems that keep the marketplace efficient, reliable, and ready for continued growth. Our systems power hundreds of millions of consumers and millions of merchants around the world, and that footprint is expanding rapidly.
What You'll Do
- Design and build innovative products used by hundreds of millions of consumers, in collaboration with talented engineers, Product Managers, Product Operations, and Applied/Data Scientists
- Develop and optimize ML models to enhance the efficiency of key delivery marketplace pricing levers
- Build offline data pipelines using Hive or similar technologies
- Write clean, maintainable, and high-quality code
Basic Qualifications
- Completing or recently completed a PhD in Statistics, Mathematics, Computer Science, Machine Learning, or related quantitative field
Preferred Qualifications
- Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods
- Strong sense of ownership and accountability
- Strong problem-solving skills, with expertise in ML methodologies
Ability to thrive in a fast-paced, collaborative, and team-oriented environment
For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 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. More details can be found at the following link https://jobs.uber.com/en/benefits.
Sample Uber interview questions
- 1
Design a truck tracking system that supports filtering by truck number and includes an interface
system designmedium - 2
Design Uber Eats
system designmedium - 3
Given a sorted array of integers (which may include negatives), return the squares of the numbers
codingmedium - 4
Find the minimum characters to insert to make a string a palindrome
codingmedium - 5
Given an array of integers and a number N, find the length of the longest contiguous subarray such
codingmedium
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