The People eXperience and Technology (PXT) Central Science Team uses economics, behavioral science, statistics, Machine Learning, and LLMs to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We invest in innovation and rapid prototyping of scientific models and software solutions to accelerate informed, accurate, and reliable decision backed by science and data.

Our team builds distributed, scalable, and highly available systems that make Machine Learning (ML), LLM, Econometrics/Statistical/Causal models run faster in a CI/CD fashion. We own products ranging from Data Lakes to tools for science experimentation, MLOps, GenAIOps, and analytics to web applications and software solutions integrated with other Amazon systems. Robust and user-friendly software solutions, and data security and privacy are our top concerns.

We're seeking a Software Development Engineer (SDE) specializing in managing large volumes of data within an MLOps/GenAIOps framework. Desired expertise includes familiarity with Machine Learning lifecycle management, encompassing model training, validation, debugging tools, analysis techniques, and enhancing LLM responses through methodologies like RAG, Prompt Engineering. The perfect fit will possess robust software engineering fundamentals, adeptness in system architecture, a strong grasp of machine learning principles, and the capability to construct scalable systems that streamline model deployment and GenAI application building. Exposure to ML system design, frameworks, GenAI application design/development and industry best practices would be advantageous.

As a Software Engineer, you'll team up with economists, academic scholars, machine learning experts, and fellow developers throughout the company. Together, you'll craft, experiment, and launch services embodying diverse scientific models. This involves leveraging intricate distributed systems, handling and presenting Big Data, and applying advanced statistical methods. The ideal candidate will thrive on innovation, embrace leading-edge tech, and relish contributing to a high-impact field.

This position can be located in Seattle, Bellevue, Sunnyvale, Austin, or Arlington.