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.

Optimization Engineers lead efforts within the team and broader Delivery Marketplace organization to drive ideation, development and productionization of optimization solutions with real-time and ML-based signals that solve strategically important problems. Some existing problem spaces that the team works on:

• Using statistical/machine learning/forecasting models for demand and supply models
• Develop the objective function which balances magical user experience and economics of the business
• Design dispatch timing algorithms

It is a challenging yet rewarding job. You will have a lot of opportunities to work with product managers, data scientists and engineers from other teams. You will be in charge of solving Uber-scale problems with the right techniques like reinforcement learning, deep learning, and optimization methods.

• What You Will Do

• You will build new scalable algorithms for real-time delivery matching products across hundreds of global marketplaces.

• You will take things from mathematical formulation through to prototype and experiment to production.

• You will help identify new opportunities for improving our algorithms and models

• Basic Qualifications

• Bachelors (or higher) in Computer Science, Engineering, Mathematics or a related field

• Experience in programming with a language such as Python, C, C++, Java, Go, etc.

• Experience with SQL and database systems such as Hive, Kafka, Cassandra, etc.

Preferred Qualifications:

• 1 year or more of industry experience developing algorithms and optimization models for large-scale deployment.

• Experience with two or three-sided marketplace design, matching/allocation, pricing optimization, etc

• Familiarity with Machine Learning models, experimentation (e.g., A/B testing) and causal inference

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

• Strong communication skills and ability to work effectively with cross-functional partners.

• For New York, NY-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.

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.