About the Role

Delivery Marketplace is a central pillar to Uber's delivery products. As the central brain of the company, we are the decision makers that make moving from point A to point B possible for every order that Uber serves, from Uber Eats to new verticals such as Grocery. We handle all the logic from making the dispatch decisions, predicting how long a delivery might take, and estimating optimal pickup times for orders. We build products that directly impact Uber's top and bottom lines.

Senior Staff Optimization Engineers spearhead strategic initiatives across the Delivery Marketplace and partner organizations. In this role, you will drive the end-to-end lifecycle of complex optimization solutions-from abstract ideation to production deployment. You will lead the evolution of our algorithmic stack, integrating online optimization and reinforcement learning with real-time signals to solve the company's most critical business challenges.

What You Will Do

• You will work with a mixed team of Engineers, Applied Scientists, and Product Managers.
• You will lead the design, development, optimization, and productization of solutions and systems that are used to solve strategically important or vaguely defined problems.
• You will build solutions to improve Delivery marketplace efficiency while delivering magical user experience.
• You will help set the team's technical direction and roadmap.
• You will communicate with leadership, identify new opportunities, and help guide the growth of more junior engineers.

Basic Qualifications

• Bachelors (or higher) in relevant fields (Operations Research, Industrial Engineering, Computer Science, etc).
• 8+ years of industry experience developing algorithms and models for large-scale deployment.
• Experience with optimization packages such as Gurobi, CPLEX, Tools, etc.
• Strong communication skills and ability to work effectively with cross-functional partners.
• Proficiency in one or more coding languages such as Python, Java, Go, or C++.

Preferred Qualifications

• Experience with three-sided marketplace design, dynamic pricing optimization, matching/allocation, etc.

• Familiarity with optimization modeling, machine learning models, experimentation (e.g., A/B testing), and causal inference.

• Experience with real-time optimization systems (optimization under tight time constraints).

• Experience in optimization (RL / Bayes / Bandits) and online learning.

• Experience mentoring and growing junior engineers

• Experience with creating and defining technical direction and roadmaps

• Experience in 0 to 1 projects from idea/inception through to launch

• For New York, NY-based roles: The base salary range for this role is USD**$267,000 per year**

• USD**$297,000 per year**.

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.

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.

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.