Job Title

Applied Scientist II, Geospatial Science, Last MileCustomer 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 Geospatial science team within Last Mile, you will partner closely with other scientists and engineers in a collegial environment to develop enterprise ML solutions with a clear path to business impact. The setting also gives you an opportunity to think about a complex large-scale problem for multiple years and build increasingly sophisticated solutions year over year. In the process, there will be opportunities to innovate, explore SOTA and publish the research in internal and external ML conferences. Successful candidates will have deep knowledge of competing machine learning methods for large scale predictive modelling, natural language processing, semi-supervised & graph based learning. We also look for the experience to graduate prototype models to production and the communication skills to explain complex technical approaches to stakeholders of varied technical expertise. Key job responsibilitiesAs an Applied Scientist II, your responsibility will be to deliver on a well-defined but complex business problem, explore SOTA technologies including GenAI and customize the large models as suitable for the application. Your job will be to work on an end-to-end business problem from design to experimentation and implementation. There is also an opportunity to work on open-ended ML directions within the space and publish the work in prestigious ML conferences. About the teamLMAI team owns WW charter for address and location learning solutions which are crucial for efficient Last Mile delivery planning, who also owns problems in the space of maps learning and travel time estimations. BASIC QUALIFICATIONS- 3+ years of building machine learning models or developing algorithms for business application experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing PREFERRED QUALIFICATIONS- Experience using Unix/Linux - Experience in professional software development - Master's degree, or PhD Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visitthis linkfor more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.#J-18808-Ljbffr