The On-Device Machine Learning team at Apple is seeking an ML Infrastructure Engineer focused on model compilation. This role involves collaborating with various teams to optimize machine learning models for execution on Apple hardware. The engineer will contribute to building an end-to-end developer experience for machine learning, leveraging Apple's vertical integration. This position is ideal for someone passionate about machine learning and system software engineering.

• 3-5 years of experience working on MLIR-based compilers.
• Familiarity with common ML model architectures, execution schemes, and operations.
• Proficiency in C++.
• Experience with PyTorch or related training frameworks.
• Familiarity with Swift.
• Knowledge of programming paradigms for the GPU, CPU, and Neural Engine.
• Experience in writing kernels for ML model execution.

• Work closely with model authoring, runtime, and performance teams to optimize machine learning models.
• Develop and enhance the core runtime for executing models across various devices.
• Contribute to the MLIR-based compiler stack targeting the neural engine, GPU, and CPU.
• Support the end-to-end developer experience for machine learning development.
• Iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis.

• 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.