Machine Learning Data Engineer - Systems & Retrieval
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The role
Design, build, and optimize end-to-end data pipelines for ML systems, from ingestion and transformation to indexing and serving at web-scale.
Develop retrieval and indexing systems to support RAG and large language model workflows across diverse datasets.
Collaborate with ML engineers, infrastructure, and product teams to scale pipelines and ensure data quality and reliability.
Implement secure data handling with access controls, auditing, and compliance best practices (e.g., GDPR, SOC2).
Enhance observability, debugging, and monitoring to maintain reliability at scale in production environments.
Work across raw unstructured data, structured databases, and model-ready formats to lay the data foundation for intelligent systems.
Develop retrieval and indexing systems to support RAG and large language model workflows across diverse datasets.
Collaborate with ML engineers, infrastructure, and product teams to scale pipelines and ensure data quality and reliability.
Implement secure data handling with access controls, auditing, and compliance best practices (e.g., GDPR, SOC2).
Enhance observability, debugging, and monitoring to maintain reliability at scale in production environments.
Work across raw unstructured data, structured databases, and model-ready formats to lay the data foundation for intelligent systems.
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