AI Data Platform Engineer — GenAI Data Pipelines

Apple Inc.; Cupertino (CA); On-site; USD 150,000 - 278,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Employee stock programs

Tuition reimbursement

Relocation assistance

Job summary

Apple Inc. in Cupertino, CA, is seeking an AI Data Platform Engineer to design, build, and operate scalable data platforms for GenAI, agentic AI, and Embodied AI across the enterprise.

You will create reusable services, data pipelines, and quality frameworks enabling AI-ready datasets and end-to-end data lifecycle management. You will collaborate with AI/ML engineers, software teams, and domain experts to deliver production-grade data solutions, ensure platform scalability, reliability, and cost

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• 5+ years designing and building scalable data platforms and distributed systems.
• Strong Python and SQL; Java or Scala preferred.

Responsibilities

• Design, build, and maintain scalable AI data platforms, services, and APIs for model development and deployment.
• Develop data ingestion, transformation, and publishing pipelines for structured, unstructured, and multimodal data.
• Create AI-ready datasets with ground truth, curation, annotation workflows, versioning, and metadata management.

Skills

Python

SQL

Java/Scala

Airflow

Kubeflow

MLflow

Spark PySpark

Kafka

Pandas

Cloud platforms

Education

Bachelor's or Master's in CS/Software/Data Eng

Tools

Iceberg/Delta Lake

Vector databases

RAG architectures

LLM data prep tools

Job description

Apple Inc. in Cupertino, CA, is seeking an AI Data Platform Engineer to design, build, and operate scalable data platforms for GenAI, agentic AI, and Embodied AI across the enterprise.

You will create reusable services, data pipelines, and quality frameworks enabling AI-ready datasets and end-to-end data lifecycle management. You will collaborate with AI/ML engineers, software teams, and domain experts to deliver production-grade data solutions, ensure platform scalability, reliability, and cost