On-device Machine Learning Infrastructure Engineer (Compiler & Runtime)

Key Skills

C++, Debugging, Framework, GPUs, JAX framework, ONNX, Python Programming, PyTorch, Transformer, UI design, UX design

Job Description

As an engineer in this role, you will be primarily focused on building graph compilers that optimize ML graphs coming from the most popular ML frameworks (PyTorch, JAX, MLX, etc.) to execute performantly and efficiently on Apple Silicon. The graph compiler and runtime provides out-of-the-box capability for executing ML models while also providing extensibility hooks for users to tailor specific goals. The role also has exposure to building higher level APIs and toolings to enable developers to visualize, diagnose, and debug correctness and performance issues while onboarding models to on-device deployment.

We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple’s vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The ML compiler is the backbone of such infrastructure stack.

The role requires understanding of ML operator primitives, common compiler optimizations (frontend/middle-end), runtimes, and system software engineering.

Key responsibilities:

• Define and build the on-device graph compiler, runtime, and kernels executing ML operators.
• Build production-critical system software for executing ML models on Apple Silicon.
• Optimize model execution for various system goals such as performance, energy efficiency, thermals, etc.

Minimum Qualifications

• Bachelors in Computer Sciences, Engineering, or related discipline.
• Highly proficient in C++. Familiarity with Python.
• Familiarity with Operating Systems, embedding programming, parallel programming.
• Experience with any compiler stack (MLIR/LLVM/TVM/...).
• Sound understanding of ML fundamentals, including common architectures such as Transformers.
• Good communication skills, including ability to communicate with cross-functional audiences.

Preferred Qualifications

• Experience with any on-device ML stack, such as TFLite, ONNX, ExecuTorch, etc.
• Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.) is a strong plus.
• Experience with accelerators, GPU programming is a strong plus.

Pay & Benefits

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 $143,100 and $264,200, 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.