**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 UberEats 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. MLEs 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: 1. Using statistical/machine learning/forecasting models for demand and supply models 2. State of the art prediction models for estimating food preparation times, batching quality as well as time spent by couriers at restaurants picking up items. 3. Develop objective function which balances magical user experience and economics of the business 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/optimization methods. \-\-\-\- What the Candidate Will Do ---- 1. Experience in modern deep learning architectures and probabilistic models. 2. Experience in optimization (RL / Bayes / Bandits) and online learning. 3. Experience in causal inference/personalization/ranking \-\-\-\- Basic Qualifications ---- 1. PhD or equivalent experience in Computer Science, Engineering, Mathematics or a related field and 2 years of Software Engineering work experience. 2. Experience in programming with a language such as Python, C, C++, Java, or Go. 3. Experience with ML packages such as Tensorflow, PyTorch, JAX, Scikit-Learn. 4. Experience with SQL and database systems such as Hive, Kafka, and Cassandra. 5. Experience in the development, training, productionization and monitoring of ML solutions at scale. \-\-\-\- Preferred Qualifications ---- 1. Experience in modern deep learning architectures and probabilistic models. 2. Experience in optimization (RL / Bayes / Bandits) and online learning. 3. Experience in causal inference/personalization/ranking Uber is proud to be an Equal Opportunity/Affirmative Action 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](https://forms.gle/aDWTk9k6xtMU25Y5A). 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. For New York, NY-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits). Uber is proud to be an Equal Opportunity/Affirmative Action 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](https://forms.gle/aDWTk9k6xtMU25Y5A). 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.