Amazon
Company
Software Development Engineer (Data/ML), AGI Information - Knowledge Graphs
US, CA, Sunnyvale
Job Description
The Amazon Knowledge Graph (AKG) team is re-inventing knowledge graphs for the LLM-era, developing sophisticated ML models and pipelines that enable efficient LLM grounding and power LLM-based customer experiences. 
We're looking for candidates who combine strong software engineering fundamentals with practical system development experience. You'll need to demonstrate expertise in building scalable, fault-tolerant distributed systems, with a track record of shipping production services that handle large-scale workloads. We prioritize candidates who understand professional software engineering practices across the full development lifecycle - from system design and coding standards to testing, deployment, and operational excellence.
Key job responsibilities
- Develop efficient data processing pipelines to handle large-scale training and inference data
- Support experimentation and A/B testing infrastructure to evaluate model improvements
- Participate in code reviews, technical design discussions, and sprint planning to ensure high quality software delivery
- Develop and optimize LLM-assisted tools that revolutionize knowledge graph creation, from automated ontology generation to real-time fact extraction and verification
- Architect AI/ML systems that power our billion-entity knowledge graph, transforming raw data into intelligent, interconnected information at scale
- Release and maintain ML model infrastructure to enable high-throughput, low-latency inference in production environments
- Collaborate with applied scientists to productionize ML models, and deliver new architectures for knowledge mining and graph construction
We're looking for candidates who combine strong software engineering fundamentals with practical system development experience. You'll need to demonstrate expertise in building scalable, fault-tolerant distributed systems, with a track record of shipping production services that handle large-scale workloads. We prioritize candidates who understand professional software engineering practices across the full development lifecycle - from system design and coding standards to testing, deployment, and operational excellence.
Key job responsibilities
- Develop efficient data processing pipelines to handle large-scale training and inference data
- Support experimentation and A/B testing infrastructure to evaluate model improvements
- Participate in code reviews, technical design discussions, and sprint planning to ensure high quality software delivery
- Develop and optimize LLM-assisted tools that revolutionize knowledge graph creation, from automated ontology generation to real-time fact extraction and verification
- Architect AI/ML systems that power our billion-entity knowledge graph, transforming raw data into intelligent, interconnected information at scale
- Release and maintain ML model infrastructure to enable high-throughput, low-latency inference in production environments
- Collaborate with applied scientists to productionize ML models, and deliver new architectures for knowledge mining and graph construction
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