Job Description

The On-Device Machine Learning team at Apple is seeking an ML Infrastructure Engineer to develop APIs that enable ML engineers to efficiently author and convert ML models for Apple platforms. This role involves integrating Apple's ML tools into various model repositories and optimizing the model ingestion process to enhance performance across the Apple ecosystem.

Requirements

Bachelors in Computer Sciences, Engineering, or related subject area.
Highly proficient in Python programming, familiarity with C++ is required.
Proficiency in at least one ML authoring framework, such as PyTorch, MLX, and JAX.
Strong understanding of ML fundamentals, including common architectures such as Transformers.
Hands-on experience with ML inference optimizations, such as quantization, pruning, KV caching, etc.
Strong communication skills, including ability to connect with multi-functional audiences.

Responsibilities

Develop APIs in Apple’s ML stack for ML engineers to efficiently import and implement their models.
Integrate Apple’s ML tools into internal and external model repositories to demonstrate and stress-test model ingestion with peak efficiency and performance.
Develop optimizations across the pipeline, including source-level transformations, and custom operations to improve inference efficiency.
Onboard the latest ML models with peak performance, and use these examples to highlight and validate the authoring and runtime capabilities of Apple’s inference stack.

Benefits

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.