Machine Learning Engineer

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:

• Using statistical/machine learning/forecasting models for demand and supply models
• 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.
• 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.

As a Machine Learning Engineer, you will:

• Drive the design, development, optimization, and productization of machine learning (ML) solutions and systems that are used to solve strategically important or vaguely defined problems.
• Build ML solutions to improve Delivery marketplace efficiency while delivering magical user experience

This role offers the opportunity to work on cutting-edge ML technologies at scale, solving complex problems that directly impact Uber's business and user experience. You'll be part of a team that's at the forefront of innovation in the delivery marketplace space, using advanced techniques like reinforcement learning and deep learning to optimize operations and enhance user satisfaction.