Building Scientist
3 weeks ago
Would you like to work on developing ML models for one of the largest transactional distributed systems in the world? How about working with customers and peers from the entire range of Amazon's business and Science on complex real-world problems, backed with high volume data? Whether you're passionate about building highly scalable and reliable systems or a scientist who likes to solve business problems, Amazon Tax Platform Services is the place for you.
We are responsible for the tax calculation platform, providing the core services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital, globally. We seek to provide the correct tax amounts to the customer when placing their Amazon order, and ensure all records are stored safely to meet tax law requirements around the globe. Our challenges include staying on top of the complex and ever-changing global tax legislations as well as computing calculations correctly and quickly, thousands of times a second, and each one needs to be accurate.
As an Applied Scientist, you will provide machine learning leadership to the team that helps increase the accuracy of tax classification based product information in Amazon catalogue making it the biggest and most challenging tax classification using machine learning models globally. You will work with large language models, to build various machine learning models to predict accuracy of human's on specific tasks, reason with large volumes of systems changes to identify causal determinants, and apply generative AI to model outcomes from sparse data. You will help us innovate different ways to enhance the tax classification experience for our global customers.
You will need to be entrepreneurial, work in a highly collaborative environment with SDEs, Product Managers, and businesses. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field 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
- Experience using Unix/Linux
- Experience in professional software development
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