Amazon

Applied Scientist II, Geospatial Science, Last Mile

Posted On

April 3, 2025

Location

Hyderabad, Telangana

Experience Level

Freshers/Experienced

Job Type

Machine Learning Science

Apply By

May 13, 2025

Job Description

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 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 building increasingly sophisticated solutions year over year. In the process there will be opportunity 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 the stakeholders of varied technical expertise.

Key job responsibilities
As 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 a 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 team
LMAI 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. - 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

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