layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

AI Data & Knowledge Engineer at Apple | LAYIQ

Responsible for the development and design of data pipelines and data knowledge layers for agentic AI applications.
Design and implement data models for a semantic layer that integrates analytics data from multiple sources in an efficient and effective manner.
Design and build scalable data and knowledge layers that power chatbots and other agentic applications.
Build RAG-ready data pipelines and knowledge layers encompassing document ingestion, parsing, metadata tagging, embeddings, indexing with vector search.
Design scalable architecture for semantic and hybrid search, knowledge graphs to enable contextually accurate text-to-SQL generation.
Build mechanisms for incremental synchronization of data to knowledge updates so agent responses are current and reliable.
Designing and operating distributed data systems — from SQL/NoSQL databases, Vector search, and orchestration.
Collaborate with Analytics and Data Science teams to translate business requirements into reliable, actionable knowledge layers that support AI agent development and deliver targeted business outcomes.
Collaborate with internal business partners, internal technology resources (database, system, networking), external vendors, and partners.
Play an active role in the development and maintenance of user documentation, including data models, mapping rules, and data dictionaries.
Ensure data quality and accuracy by developing data validation and reconciliation processes.
Build and maintain data pipelines for ingesting, processing, and transforming unstructured data sources, such as customer feedback, social media data, or sales call recordings.
Develop data quality monitoring and validation processes specifically for AIML datasets, including identifying and addressing data bias.
Work with data scientists to understand data requirements for AIML model training and deployment, ensuring data is available in the appropriate format and quality.
Implement data governance policies and procedures to ensure the responsible and ethical use of data in AIML applications.

AI Data & Knowledge Engineer

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