AI Data & Infrastructure 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 u0026 Infrastructure Engineer with the MSI team you will won the end to end design build and operation of scalable AI data systems that power enterprise GenAI and Agentic AI capabilities. Your work spans core platform services data pipeline development and infrastructure provisioning enabling manufacturing workflow automation through Agents and Agent skills.

Create robust scalable architectures for systems that handle data orchestration for AI featuresnnDesign build and maintain scalable AI data platforms services and APIs that support and enable Agentic AI workflow development u0026 data ingestion transformation and publishing pipelines for structured unstructured and multimodal and implement Retrieval-Augmented Generation (RAG) pipelines embedding workflows vector database integrations and metadata services for enterprise AI applications. nnBe able to quickly build an idea so you and the team can work with hands-on products. Then iterate on the best of those and integrate tools that help make complex AI systems observable understandable and debuggablennStrong understanding of distributed systems parallel computing and performance optimizationnnCollaborate 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 environments and Agentic to clearly communicate complex technical problems and collaborate with partners to develop solutions

Bachelors or Masters degree in Computer Science Software Engineering Data Engineering or a related field.n8 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).nExperience using modern development tools including AI-assisted coding tools while applying sound engineering judgment to review validate and improve generated 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 ability to understand complex user workflows translate them into practical technical solutions and collaborate across teams to deliver measurable communication and collaboration skills with the ability to translate technical concepts into clear business focused insights.

Experience with or a strong understanding of Generative AI LLMs Agentic Systems or RAG (Retrieval-Augmented Generation) integrating LLMs into existing systemsnExperience with API design both for other engineers to use but also for AI working with manufacturing operational IoT or industrial data ability to lead technical initiatives and mentor engineers.