Demand Science Optimization (DSO) organization builds supply chain software systems in the realm of Machine Learning (ML/AI/LLM) and economic modeling to address specific device-related challenges within inventory management functions: demand forecasting, pricing, and allocation. Our goal is to achieve a high level of automation, enabling a hands-off approach to assess tradeoffs such as pricing and promotion strategies, prediction and optimization services, and economic valuation. This approach aims to expedite the operational and financial leverage of Devices and Services, enhance customer satisfaction, and direct our team's expertise towards strategic decisions that have lasting implications. With a diverse product portfolio including popular devices like Alexa, Kindle, Ereader, Ring, Blink, and more, DSO faces intricate challenges.

Our software solutions wield considerable influence, as our predictive algorithms guide the allocation of billions of dollars across a multitude of distribution points globally. It is critical that Amazon accurately forecasts the demand for each device. To solve this complex problem, Amazon is looking for a passionate, talented, and customer obsessed software engineer to join the Devices Machine Learning Products (DMLP) team within DSO org. Our products materially impact Amazon’s devices businesses by forecasting demand for all Amazon Devices using Machine Learning (ML) and big data.

We are a growing team that continues to operate in startup mode to prove new business ideas, while strengthening our core ML platforms, and continuously improving our delivery of these forecasts to our customers.

Key job responsibilities
As a SDE on the Devices Machine Learning Products(DMLP) team, you will design, build & manage the custom ML Platforms and services to support Amazon Devices Forecasting. You will work closely with scientists in improving the accuracy of the existing ML models or build new models. You will help on defining the system architecture, own and implement specific components and helps shapes the overall forecasting experience.