On-device ML Infrastructure Engineer, Compiler & Runtime, Graphics, Games & ML

We are seeking an experienced ML Infrastructure Engineer with a specific focus on building the best execution engine and compilation toolchain that employs our compilers infrastructure and the world’s most efficient, portable, and extensible runtime, and which is capable of optimizing and driving ML models efficiently on Apple products and services, current and future.

This is a senior role and functions as the glue between our compiler technology, the runtime components, the kernel libraries, and the low-level hardware compilers to enable the execution of ML across a wide variety of devices and use cases. The successful candidate will make critical decisions affecting project direction and outcome.

We’re seeking a highly motivated software engineer who is creative, skilled, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning”,”responsibilities”:”

Help lead and deliver on critical initiatives for on device machine learning infrastructure.

Design, build, and maintain critical machine learning infrastructure that powers Apple’s machine learning features.

Collaborate with downstream hardware compilers to best leverage Apple’s machine learning hardware.

Collaborate with first and third party users to adopt our infrastructure and apply protocols when they implement machine learning on Apple devices.

Ensure our infrastructure can run optimally for a wide range of first and third party machine learning models.

Do you have experience in Swift?, Experience with any on-device ML stack, such as TFLite, ONNX, ExecuTorch, etc.

Experience with open source machine learning models (Mistral, Phi, Gemma, Huggingface, etc)

Experience with any compiler stack (MLIR/LLVM/TVM/…).

Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.).

Experience with machine learning accelerators and GPU programming., Bachelors in Computer Science, Engineering, or related subject area and 5+ years of hands on experience.

Highly proficient in C++. Familiarity with Python and Swift.

Familiarity with Operating Systems and Embedded Programming.

Sound understanding of ML fundamentals, including common architectures such as Transformers.

Good communication skills, including ability to communicate with multi-functional audiences.

4.14.1 out of 5 stars Cupertino, CA $181,100 - $318,400 a year, Pulled from the full job description

• Employee stock purchase plan
• Health insurance
• Retirement plan
• Dental insurance
• RSU, 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 $181,100 and $318,400, 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.

Imagine being at the forefront of an evolution where modern 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 powerful 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.

We’re building an end-to-end developer experience for machine learning development that brings to bear Apple’s vertical integration. This allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis. If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful cluster, 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.