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.

📌 Applied Scientist Tax Machine Learning (Vancouver)
🏢 Amazon
📍 Vancouver