The ML Infrastructure Engineer role focuses on model compilation within the On-Device Machine Learning team at Apple. This team is dedicated to transforming research into practical applications that enhance the performance of AI models on Apple devices. The engineer will work closely with various teams to ensure optimal execution of machine learning models across different hardware. This position offers an opportunity to contribute to the next generation of intelligent experiences on Apple platforms.

• 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 writing kernels for ML model execution.

• Collaborate with model authoring, runtime, and performance teams to optimize model execution.
• Develop and maintain the core runtime for machine learning execution across various devices.
• Contribute to the end-to-end developer experience for machine learning development.
• Utilize the MLIR-based compiler stack to target the neural engine, GPU, and CPU.
• Work on model 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.