DESCRIPTION
Job summary
Customer addresses, Geospatial information and Road-network play a crucial role in Amazon Logistics' Delivery Planning systems. We own exciting science problems in the areas of Address Normalization, Geocode learning, Maps learning, Time estimations including route-time, delivery-time, transit-time predictions which are key inputs in delivery planning. As part of the Last Mile Science & Technology organization, you'll partner closely with other scientists and engineers in a collegial environment to develop enterprise ML solutions with a clear path to business impact. We are actively looking to hire scientists at various levels to innovate and lead on these problem areas. Successful candidates will have deep knowledge of competing machine learning methods for large scale predictive modelling and natural language processing, the ability to graduate models to production, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the ability to take iterative approaches to tackle big, long term problems.
Here is a glimpse of the problem spaces and technologies that we deal with on a regular basis:
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