AI Data Platform Engineer

Imagine what you could do here. At Apple we believe new insights have a way of becoming excellent products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could people here at Apple dont just build products they build the kind of wonder thats revolutionized entire industries. Its the diversity of those people and their ideas that inspires the innovation that runs through everything we do from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found Systems and Infrastructure (MSI) team is an engineering organization under the Product Operations org. MSI is responsible for the design development and maintenance of systems tools services and applications required to efficiently run manufacturing operations at scale across global factory an AI Data Platform Engineer with the MSI team you will design build and operate scalable AI data platforms that enable GenAI Agentic AI and Embodied AI solutions across the enterprise. You will develop reusable platform services data pipelines and data quality frameworks that transform fragmented enterprise and multimodal data into trusted AI-ready datasets combining expertise in AI data platform engineering data quality systems engineering and AI data lifecycle management to accelerate AI innovation.n

Design build and maintain scalable AI data platforms services and APIs that support and enable AI model development and data ingestion transformation and publishing pipelines for structured unstructured and multimodal AI-ready datasets through ground truth creation data curation annotation workflows dataset versioning and metadata data quality frameworks validation pipelines observability and evaluation metrics to ensure trusted AI and implement Retrieval-Augmented Generation (RAG) pipelines embedding workflows vector database integrations and metadata services for enterprise AI scalable platform capabilities for managing the end-to-end AI data lifecycle including ground truth dataset creation dataset versioning metadata and lineage management automated data quality validation governance and secure publishing of AI-ready with AI/ML engineers software engineers product teams and domain experts to define AI data requirements and deliver production-ready data platform scalability reliability performance security and cost across cloud-native engineering best practices for AI data architecture platform design automation testing monitoring and operational emerging AI technologies and continuously improve platform capabilities that enable GenAI agentic AI and embodied AI solutions.

Bachelors or Masters degree in Computer Science Software Engineering Data Engineering or a related field.n5 Experience designing and building scalable data platforms and distributed programming skills in Python and SQL with proficiency in Java or Scala with Airflow Kubeflow or MLflow to build and orchestrate scalable AI data building scalable batch and streaming data pipelines using Spark (PySpark) Kafka Airflow and Ray with proficiency in Pandas and modern data lake/lakehouse architectures (e.g. Iceberg Delta Lake).nHands-on experience with AI data engineering including ground truth dataset creation data curation annotation pipelines dataset versioning and metadata implementing data validation quality frameworks observability and AI dataset of RAG architectures embedding generation vector databases and AI data preparation for LLMs and agentic with cloud platforms (AWS Azure or GCP) Kubernetes Docker CI/CD and Infrastructure as understanding of distributed systems APIs microservices and enterprise integration communication collaboration and technical leadership skills.

Experience building platforms supporting GenAI Agentic AI or Embodied AI with multimodal datasets knowledge graphs AI evaluation frameworks or vector search with enterprise data governance lineage metadata management and AI working with manufacturing operational IoT or industrial data ability to lead technical initiatives and mentor engineers.