Apple · Seattle

On-device ML Performance Infrastructure Engineer

(w/m/d) · 22.5.2025

Description

As an engineer in this role, you will be primarily focused on building performance infrastructure to present high level views of ML inference behavior which are created by gathering lower level data from execution delegates and relating the data to the high level model. You’ll work with models created by the most popular ML frameworks (PyTorch, JAX, MLX, etc) and will analyze the execution to ensure the stack achieves full machine performance on Apple Silicon. 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. Providing actionable feedback to ML developers w.r.t. the details of their model’s inference behaviors is crucial to achieving full machine performance. The role requires understanding of ML architectures, compilers, runtimes, system performance, and system software engineering. Key responsibilities: * Build production-critical system software for tracking low level details of executing ML models on Apple Silicon and then associating this with ops from high level models. * Optimize model execution for various system goals such as performance, memory, energy efficiency, etc. * Contribute to maintaining the health and performance of the ML benchmarking service, including debugging failures and addressing user questions / requests.

Qualifications

  • Highly proficient in C++. Familiarity with Python.
  • Familiarity with Operating Systems, embedding programming, parallel programming.
  • Knowledge of ML fundamentals including training regimes, evaluation and deployment/inference.
  • A passion/interest for ML, particularly applied to on-device use cases.
  • Good communication skills, including ability to communicate with cross-functional audiences.

Preferred Qualifications

  • Masters or PhDs in Computer Science or relevant disciplines.
  • On-device ML stack, such as TFLite, ONNX, ExecuTorch, etc.
  • ML authoring framework (PyTorch, TensorFlow, JAX, etc.).
  • Compiler stack (MLIR/LLVM/TVM etc.).
  • Accelerators and GPU programming.
  • OS kernel programming, computer architecture or performance analysis
  • Developer tools such as vTune and Nvidia Nsight
  • ML architectures such as Transformers, CNNs or Stable Diffusion a strong plus.

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 $135,400 and $250,600, 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.

Application

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