Machine Learning Engineer, AGI Information - Knowledge Graphs

Amazon's AGI Information team is seeking an exceptional Machine Learning Engineer to join their Amazon Knowledge Graph (AKG) team. This role sits at the intersection of cutting-edge AI technology and large-scale distributed systems, focusing on reinventing knowledge graphs for the LLM era. The position combines software engineering excellence with machine learning expertise, working on sophisticated ML models and pipelines that enable efficient LLM grounding and power LLM-based customer experiences.

The role involves architecting and developing AI/ML systems that manage a billion-entity knowledge graph, transforming raw data into intelligent, interconnected information at scale. You'll be responsible for developing LLM-assisted tools for automated ontology generation, real-time fact extraction, and verification. The position requires expertise in building scalable, fault-tolerant distributed systems and handling large-scale workloads.

As a Machine Learning Engineer at Amazon, you'll collaborate with applied scientists to productionize ML models, implement model improvements, and develop new architectures for knowledge mining and graph construction. The role emphasizes both technical excellence and practical implementation, requiring strong software engineering fundamentals across the full development lifecycle - from system design to operational excellence.

This is an exciting opportunity to work at the forefront of AI technology, specifically in the domain of knowledge graphs and large language models, while building systems that operate at Amazon's scale. The position offers competitive compensation, including a base salary range of $129,300 to $223,600 depending on location, plus equity and comprehensive benefits. Join Amazon's AGI Information team to help shape the future of knowledge representation and AI systems.