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Apple is seeking a Software Engineer to design and build the next generation of Applied Machine Learning Data Platforms. You will work on scalable data pipelines, data warehousing, and analytics to support ML models and large-scale inference across Apple services.
You will apply hands-on experience with Spark, Trino, Flink, Python, and SQL in a cloud-based, high-concurrency environment. Join a team driving data-driven decisions across Apple platforms and manufacturing.
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.