On-Device ML Compiler Engineer, Model Compilation, Graphics, Games and Machine Learning

Apple Inc.; Cupertino (CA); On-site; USD 185,000 - 325,000; Full time

Job summary

Apple Inc. in Cupertino, California, is seeking an On-Device ML Compiler Engineer to advance the MLIR-based compiler stack, enabling efficient execution of ML models across Apple devices—from Apple Watch to Mac Ultra SoCs.

The role focuses on model compilation, runtime optimization, and tight collaboration with hardware and performance teams to harness the full capabilities of Apple silicon for private, local AI inference.

Qualifications

• 3–5 years working on MLIR-based compilers.
• Familiarity with common ML model architectures, execution schemes, and operations.
• Familiarity with C++.
• Familiarity with PyTorch or related training frameworks.

Responsibilities

• Inspire changes in our MLIR-based compiler to target improved runtime performance across devices.
• Propose upstream MLIR changes to support new hardware features and workflows.
• Own core pieces of the compiler stack enabling heterogeneous compute from watches to Macs.
• Collaborate with hardware, software, and performance teams to optimize execution on latest hardware, OS, and drivers.

Skills

MLIR compiler

C++

PyTorch

ML model architectures

Tools

MLIR

Swift

Job description

On-Device ML Compiler Engineer, Model Compilation, Graphics, Games and Machine Learning

Cupertino, California, United States Machine Learning and AI

Imagine being at the forefront of an evolution where innovative AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation. Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding innovative architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple’s machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem. If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful clusters, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents a great opportunity to work on the next generation of intelligent experiences on Apple platforms. Our group is seeking an ML Infrastructure Engineer, with a focus on model compilation. The role entails working closely with model authoring, runtime, and performance teams to ensure that models can bring to bear the full capabilities of the hardware.

Description

We’re building an end-to-end developer experience for machine learning development that employs Apple’s vertical integration. This allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis. This role focuses on the core runtime for execution across a wide variety of devices and use cases. We’re seeking a highly motivated software engineer who is creative, versatile, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning. We have an MLIR-based compiler stack, and use it to target the neural engine, GPU, and CPU in order to harness the full capabilities of the system for ML workflows and execution.

Responsibilities

• Inspire changes in our MLIR-based compiler in order to target improved runtime performance by demonstrating the capabilities of the hardware.
• Propose upstream changes in MLIR to better support new features and workflows in the hardware that lead to more optimal execution performance across all types of devices and device clusters.
• Own core pieces of the compiler stack enabling heterogeneous compute across Apple devices. We target execution of ML models across the Apple ecosystem from resource-constrained devices like Apple Watch, to the high-end Macs with Ultra SoCs.
• Work closely with hardware, software, and performance teams across the company to accelerate and optimize execution by taking advantage of the latest features in the hardware, OS, and drivers.

Minimum Qualifications

• 3-5 years working on MLIR-based compilers.
• Familiarity with common ML model architectures, execution schemes, and operations.
• Familiarity with C++
• Familiarity with PyTorch or related training frameworks

Preferred Qualifications

• Familiarity with Swift.
• Familiarity with programming paradigms for the GPU, CPU, and Neural Engine.
• Familiarity with writing kernels for ML model execution.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple’s workplace Learn about reasonable accommodations for job applicants