Build machine learning models for Amazon Tax Platform Services, applying large language models and generative AI to tax classification accuracy. Solve complex business problems with high-volume data.
As an Applied Scientist, you will provide machine learning leadership for tax classification using product information from Amazon’s global catalogue. You will develop models that predict human performance on specific tasks, identify causal determinants across systems and legislative changes, and model outcomes from sparse data. The work supports tax calculations for Amazon sales worldwide.
Key Responsibilities: Build machine learning models for tax classification accuracy
Apply large language models to complex tax problems
Use generative AI to model outcomes from sparse data




Reason across systems and legislative changes
Enhance tax classification experiences for global customers
Requirements: Three-plus years building models for business applications
PhD, or master’s degree with four-plus years’ experience
Experience in computer science, computer engineering, machine learning, or related fields
Patents or publications in top-tier peer-reviewed venues
Programming experience in Java, C++, Python, or related languages
Apply algorithms, programming, machine learning, and generative AI to advance Amazon’s global tax classification platform.

#J-18808-Ljbffr

📌 Applied Scientist Tax Machine Learning (British Columbia)
🏢 Amazon
📍 British Columbia