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Apple
Cupertino, California
Source: Apple careers · View original posting
From Apple's posting. “We” and “our” refer to the employer.
The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting edge machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that discipline, interfacing with research, SW engineering, HW engineering, and products.
The On-device ML Performance team has the responsibility to analyze latency, memory, power and numerical correctness of the latest machine learning models running on Apple SoC’s, and to make Apple’s ML software stack take full advantage of the capabilities in Apple’s ML accelerators. The work from this cross functional team enables model developers’ decisions to optimize performance via advanced techniques such as different model authoring techniques, quantization, sparsity, performance and accuracy tradeoffs.
The work of this team impacts all new Apple HW and ML Inference on them.
Our group is looking for an On-device ML Performance Engineer, with technical expertise in computer architecture, performance, memory, power, ML model architectures, ML frameworks such as PyTorch, and on-device ML inference. The role entails deep analysis of ML models and their architecture, the implementation of the models in the ML SW stack for optimum performance, power and memory usage, and debug involving the performance and power consumption of CPU, GPU, and Apple Neural Engine.
Description
As an engineer in this role, you will be primarily focused on analyzing and optimizing the performance of the latest ML models on the latest iPhones and Mac’s. You will work with models created by the most popular ML frameworks (PyTorch, MLX, etc) and will analyze the inference of those models on device to ensure the stack achieves full machine performance on Apple Silicon.
The role also includes scripting, coding, model import and conversions, and generation of utilities and debug tools to extract, analyze, and report performance and power related metrics for Apple HW. The ideal candidate will have a passion for ML model architectures and ML inference, deep knowledge of GPU and CPU, computer architecture, compilers, and has a natural inclination toward innovation and exploration.
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 $150,400 and $277,600, 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.
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