Senior Machine Learning Engineer, Applied Science and AI, NACF ACES
Amazon
DESCRIPTION
The ACES Applied Science and AI team is seeking a Senior Machine Learning Engineer to join our team of Applied and Data Scientists to lead the end-to-end development of Generative AI (GenAI) products. You'll architect and implement solutions for complex operational challenges using state-of-the-art SDK and Agentic Frameworks (Strands, LangGraph, LangChain, CrewAI) and Large Language Models (LLMs). We are building multiple autonomous and ambient agents that process GB-scale live data from Amazon's internal tools, serving numerous customers across our Fulfillment Centers (FCs) Network to improve our customers’ productivity and streamline operations.
Key job responsibilities
The role encompasses full-stack development of GenAI applications in partnership with senior scientists and other software developers, including:
* Partnering with team to investigate design approaches and evaluating technical feasibility
* Designing and implement scalable architectures for GenAI applications using AWS services in a production environment.
* Developing understanding of emerging technologies and algorithms in the field of Generative AI.
* Building Model Context Protocol (MCP) servers for internal tools.
* Building interactive front-end applications for user interaction with agents - browser extensions/backend services on AWS
* Developing robust backend systems for storage, retrieval, logging, analytics, and context management
* Collaborating with cross-functional teams of technical product managers and SMEs from ideation to deployment.
About the team
The ACES Applied Science and AI (ScAI) team delivers Generative AI, Machine Learning, and LLM powered Causal solutions to solve business problems across North America Customer Fulfillment (NACF). From machine learning modeling to automation, we deliver impactful science and software solutions to enhance business efficiencies, improved decision-making, simplify operational complexity while driving measurable results.