Machine Learning Engineer, AGI - Amazon Knowledge Graph

Amazon.com, Inc.•Sunnyvale, CA

36d

About The Position

Amazon's AGI Information is seeking an exceptional Software Development Engineer to drive advancements in the Amazon Knowledge Graph (AKG) Construction and Retrieval infrastructure. AKG is re-inventing knowledge graphs for the LLM-era, optimizing for LLM grounding and enabling agentic AI systems that require real-time knowledge retrieval. AKG serves as the foundational knowledge layer for Nova and Alexa+, providing structured, factual information that grounds LLM responses and powers autonomous agent decision-making across Amazon surfaces. As a member of the AKG Interfaces team, you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in automating gap detection, data ingestion, fact verification, query optimization, entity resolution, and building scalable APIs that serve billions of requests from agentic systems.

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience programming with at least one software programming language
4+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

Nice To Haves

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent
Experience working with ML frameworks such as Pytorch, TensorRT, Onnx, AWS Neuron and accelerating deep learning models for GPU/CPU/Inferentia architectures.

Responsibilities

Build a scalable information grounding infrastructure that provides grounding evidence to multiple Amazonian experiences and agentic AI systems. Grounding large language models (LLMs) and AI agents ensures that their interactions with users are informed, relevant, consistent, and trustworthy. It ensures accuracy and relevance by providing context-specific responses and mitigating the risk of generating false information through techniques like Retrieval-Augmented Generation (RAG).
Design & Write code: Write code primarily in Java and design scalable, fault tolerant and distributed applications running on AWS technology. Leverage state of the art AWS resources in the development of a scalable web grounding service for LLM based applications.
Troubleshoot and fix operational problems: You will work with systems engineers to troubleshoot operational problems and fix them. If you are so inclined, you will also automate troubleshooting procedures and write tools. And when the issues concern specific customers, you will also have the opportunity to talk to them and understand their space better.
Influence product direction: You will propose your ideas for the future of the space to product management and get to shape the roadmap.
Hire and mentor others: You will get to interview people for the team and to mentor other engineers.

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