Software Engineer - Data Solutions, AI & Data Platform (AiDP)
Apple Sunnyvale, California, United States
Computers and Electronics Manufacturing · 10,001+ employees
About the role
You will design, build, and enhance a scalable data platform to support machine learning and analytics at a multi-petabyte scale. The role involves developing data pipelines and foundational tools to streamline AI adoption and data processing across various Apple platforms.
What they look for
Requirements
Candidates must have a bachelor's degree in a related field and at least 4 years of experience in data engineering, big data, and analytics. Proficiency in Spark, Trino, Flink, Python, and SQL is required, along with experience in high-volume, high-concurrency platform environments.
Full 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.
Description
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.
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.
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
