AI Data Platform Engineer

Apple Inc

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$150,400–$277,600 / yr
Posted
88 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $174k
This role $214k
$112k $295k
below market most similar roles pay here above market

This role pays more than 73% of similar roles. Most pay $130,153–$217,137 — the blue band above. At the midpoint, this role pays about $214k versus about $174k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · AI Data Platform Engineer

The AI Data Platform Engineer joins the Manufacturing Systems and Infrastructure team to design, build, and operate scalable AI data platforms. This role focuses on enabling GenAI, Agentic AI, and Embodied AI solutions by developing reusable platform services, data pipelines, and quality frameworks. You will transform fragmented multimodal data into trusted, AI-ready datasets through ground truth creation, annotation workflows, and metadata management. Key responsibilities include implementing Retrieval-Augmented Generation pipelines, embedding workflows, and vector database integrations. You will utilize Python, SQL, Java, or Scala alongside tools like Spark, Kafka, Airflow, Kubeflow, and Ray. The work involves managing the end-to-end AI data lifecycle, including versioning, lineage, and governance, to solve complex data preparation problems for large-scale manufacturing operations and enterprise AI applications across cloud-native environments.

What you'll do

  • Design, build, and maintain scalable AI data platforms, services, and APIs to support AI model development.
  • Develop data ingestion, transformation, and publishing pipelines for structured, unstructured, and multimodal data.
  • Build AI-ready datasets through ground truth creation, data curation, annotation workflows, and dataset versioning.
  • Develop data quality frameworks, validation pipelines, observability, and evaluation metrics to ensure trusted datasets.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, and vector database integrations.
  • Manage the end-to-end AI data lifecycle, including metadata management, lineage, governance, and secure publishing.
  • Optimize platform scalability, reliability, performance, security, and cost across cloud-native environments.
  • Evaluate emerging AI technologies to improve platform capabilities for GenAI, agentic AI, and embodied AI.

What we're looking for

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
  • Experience designing and building scalable data platforms and distributed systems.
  • Strong programming skills in Python and SQL, with proficiency in Java or Scala (preferred).
  • Experience with Airflow, Kubeflow, or MLflow to build and orchestrate scalable AI data pipelines.
  • Experience building scalable batch and streaming data pipelines using Spark (PySpark), Kafka, Airflow, and Ray with modern data lake architectures.
  • Hands-on experience with AI data engineering, including ground truth creation, data curation, annotation pipelines, and dataset versioning.
  • Experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and Infrastructure as Code.
  • Experience building platforms supporting GenAI, Agentic AI, or Embodied AI applications (preferred).

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