Principal Machine Learning Scientist Amazon
Seattle, WA

Job Description

The Inventory Planning & Control (IPC) group within Supply Chain Optimization Technologies (SCOT) is looking for a Principal Machine Learning Scientist to apply cutting edge machine learning techniques across its systems.

IPC tackles some of the most mathematically complex inventory management challenges in the industry to improve Amazon's operational efficiency worldwide. We own Amazon's global inventory planning systems - our automated systems control and optimize what, when, where, and how much IPC should buy to meet Amazon's business goals and to make customers happy. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization and simulation. Team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, economists and software engineers in the business.

As a Principal Machine Learning Scientist, we will look to you to define an agenda for how to apply cutting-edge machine learning techniques to our systems, such that our system of decentralized models behave as a single organism, adapting and correcting itself as it finds more information. We will also expect you to develop new opportunities where we can leverage machine learning and our systems to improve outcomes for our customers. In short, we will expect you to be a leader, and the opportunity we will give you is to have unparalleled impact on Amazon and its customers.