The Applied Machine Learning team at Apple is seeking a Machine Learning Platform Engineer to design and build robust, high-performance platforms for Data, Machine Learning, and Generative AI initiatives. This role focuses on creating scalable solutions for large-scale distributed systems and enhancing the efficiency and reliability of ML workloads. The engineer will lead the technical direction of ML/Data/Inference platform capabilities and work closely with cross-functional teams to influence technical strategy. This position is crucial for driving innovation and operational excellence within Apple's enterprise ecosystem.

• 5+ years of experience in software development, with a strong focus on backend systems and APIs.
• 2+ years of experience working with LLMs and Agent Frameworks.
• 5+ years of experience with cloud platforms such as AWS or GCP.
• Experience engineering scalable solutions for data processing and model training/fine-tuning workflows.
• Hands-on experience building with distributed data technologies for ML training such as Spark, Flink, Iceberg, or Snowflake.

• Design and build systems that power Data, Machine Learning, and Generative AI initiatives.
• Architect and engineer robust, high-performance, massively scalable platforms.
• Own the technical direction of ML/Data/Inference platform capabilities.
• Lead the evaluation and integration of cutting-edge open-source technologies.
• Collaborate closely with cross-functional engineering and business teams.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.