Machine Learning Architect, Platform Architecture

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$212,000–$386,300 / yr
Posted
2 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $214k
This role $299k
$146k most similar roles pay here $412k

This role pays more than 96% of similar roles. Most pay $177,762–$249,750 — the shaded band above. At the midpoint, this role pays about $299k versus about $214k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1793 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1452 roles with salary data.

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At a glance

TL;DR · Machine Learning Architect, Platform Architecture

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As a Machine Learning Architect in Apple’s Platform Architecture group, you will work at the cutting edge of hardware-software integration, focusing on optimizing machine learning applications across Apple silicon. Your daily tasks include creating efficient implementations of ML workloads on various components like Neural Engine, GPU, and CPU, collaborating with IP and SoC architecture teams to develop performance models for future hardware, and evaluating emerging optimization techniques through experimentation. You will need expertise in C/C++ or Python, experience with ML frameworks such as PyTorch, and a deep understanding of hardware IPs including accelerators and processors. This role requires strong analytical skills and the ability to communicate effectively across multidisciplinary teams to drive innovative solutions for Apple’s advanced system-on-chip architecture.

Skills

Python C/C++ PyTorch GPU CPU Neural_Engine ML_frameworks Performance_models Simulations Hardware_IPs Verilog System_architecture_trade-offs Compilers

What you'll do

  • Create optimized implementations of ML workloads on Apple silicon.
  • Develop performance models and simulations for future hardware with IP and SoC teams.
  • Analyze system architecture trade-offs for emerging ML techniques.
  • Evaluate and propose new ideas based on ML model optimization techniques from literature.
  • Provide guidance to software and algorithm teams on efficient workload execution.

What we're looking for

  • Bachelor’s degree in a relevant field.
  • Experience with C/C++ and Python programming languages.
  • Proficiency in hardware IPs like ML accelerators, GPUs, CPUs.
  • Expertise in machine learning frameworks such as PyTorch.
  • MS or PhD in Electrical Engineering, Computer Science, or related field.
  • Ability to prototype algorithms on various hardware platforms.

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