Job Description

AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning — including generative AI — along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.

We are looking for a Software Engineer to help build next- generation of Applied Machine Learning Data Platforms. Applied Machine Learning Data Platform team provides platform engineering, data engineering tools, data pipelines, and services for various Machine Learning and Analyst teams. These help to train and deploy inference models, and run data analytics at scale to prevent Fraud and automate decisioning on multiple Apple Platforms like Apple Pay, Apple Media Products, App Store, Online Store, Retail, AppleCare and Manufacturing. Our team within the greater AiDP team is the Core Platform Engineering team which is a backbone of the platform, responsible for handling data at multi-petabyte scale with low latencies and high concurrency.

We're looking for a Software Engineer with a strong data background and deep platform-thinking to design, build, and enhance a scalable, efficient data platform.

You'll bring hands-on experience in data warehousing and analytics, and thrive on solving hard, large-scale data problems. If you're passionate about building production-grade platforms and want to make a lasting impact at scale, we'd love to talk to you.

Preferred Qualifications

Building highly scalable data engineering platform components and foundational tools in Python, Java, or Scala.
Deep experience working with AI models and tools such as Claude, building agents etc
Experience with large scale platform migration projects
Working with distributed frameworks including Apache Kafka and Apache Spark and Flink and knowledge of Cloud platforms and technologies

Minimum Qualifications

Bachelor's degree or equivalent in Computer Science, Information Systems, or a related field.
4+ years of subsequent data engineering experience across the required skills.
4+ years experience working in the data warehousing, big data and analytics domains
Deep understanding and experience of working with high volume, high concurrency platforms
Writing Spark, Trino, Flink code, Python and SQL for large scale relational data warehouses and data lake platforms on the cloud.
Designing data pipelines for structured and semi-structured data.