Graduate 2026 PhD Software Engineer II (Consumer Structural Pricing), United States

San Francisco, CA, US • Posted 8 hours ago • Updated 8 hours ago
Full Time
On-site
USD $171,000.00 - 190,000.00 per year
Fitment

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Job Details

Skills

  • Real-time
  • Pivotal
  • Pricing
  • Apache Hive
  • Statistics
  • Mathematics
  • Computer Science
  • Deep Learning
  • Accountability
  • Problem Solving
  • Conflict Resolution
  • Machine Learning (ML)
  • Law
  • Legal
  • Collaboration

Summary

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 [](;br>
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](;br>
Offices continue to be central to collaboration and Uber's 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90958168
  • Position Id: cb6c81b982f70456c6493f43342bfad0
  • Posted 8 hours ago
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