SoftwareDevelopmentEngineerII,Geospatial

Are you fascinated with the idea of creating a digital representation of the world? What about building learning systems to create the most precise and accurate representation? Join the Geospatial team to build Maps for Amazon. We build learning systems to identify road networks, POIs, and geocodes of addresses worldwide. Our delivery operations use these systems to determine the locations and plan the routes for delivery. Drivers use these systems to navigate to the delivery locations. Our mission is to vend geospatial data (e.g. maps, traffic, addresses, and locations/geocodes) that is detailed and fresh through an intuitive experience that enables every driver – independent of tenure and affinity – to succeed in their delivery tasks. We are not creating another consumer-grade mapping solution, we are building systems that enable depth focused solutions. For example, we are interested in not only getting a person to an address like 300 Boren Ave N, we are also interested in guiding them where to park, where the building entrance, find out if there is a mailing room in the building that is open at that time, and guide them to alternative delivery location at the customer unit based on various factors. The level of detail we provide on the delivery journey is leading in the mapping industry. Our geocodes also dictate how to optimally group the packages for that stop based on proximity and walk times, which significantly impacts route plan and stop plan efficiencies. Several of these problems require us to build systems that can work with an ensemble of ML models as well as support the right segmentation of inputs to make good estimates on the outputs. There are several unsolved or partially solved problems in this space; such as parsing and managing both structured and unstructured addresses in various countries, modeling building entrances and unit access in multi-unit buildings, optimal polygonal geofence guardrails, and multiple delivery locations with business a