Job Description

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

BASIC QUALIFICATIONS

- 3+ years of non-internship professional software development experience
- Bachelor's degree in computer science or equivalent
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Experience with data processing and ETL pipelines at scale (Spark, GlueJob, Kafka)

Job Tags

Full time,

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