Large Machine Learning Model Optimization Engineer, SIML

Apple Inc

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$139,500–$258,100 / yr
Posted
28 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $222k
This role $199k
$124k most similar roles pay here $280k

This role pays less than 64% of similar roles. Most pay $194,000–$249,750 — the shaded band above. At the midpoint, this role pays about $199k versus about $222k for comparable roles.

Based on 239 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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Large Machine Learning Model Optimization Engineer, SIML

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As a Machine Learning Model Optimization Engineer at Apple’s SIML team, you will join an innovative research and engineering group dedicated to advancing real-time on-device technologies such as Language, Computer Vision, and Machine Perception. Your primary responsibilities include implementing optimization techniques for large language and diffusion models to enhance their performance on devices, collaborating with various teams across Apple to integrate these optimizations into user experiences, and contributing to the broader ML model lifecycle. You will leverage Python and a deep understanding of hardware-aware model optimizations, including quantization, pruning, and distillation, to deliver cutting-edge solutions that push the boundaries of what is possible in mobile AI. This role requires expertise in large-scale machine learning projects, experience with distributed inference, and a track record of publishing novel research at top conferences.

Skills

Python model compression quantization pruning distillation diffusion models language models hardware-aware model optimizations ML compiler high performance kernel implementation distributed inference

What you'll do

  • Develop and implement model compression techniques for large language and diffusion models.
  • Optimize machine learning models to enhance real-time performance on Apple devices.
  • Lead the execution of hardware-aware model optimizations across various projects.
  • Collaborate with cross-functional teams to integrate ML models into user experiences.
  • Publish novel research in top machine learning conferences and journals.
  • Drive the development of efficient ML model deployment strategies for on-device use.

What we're looking for

  • Experienced in developing large computer vision and machine learning models.
  • Proficient in hardware-aware model optimizations for efficient deployment.
  • Familiar with model compression techniques such as quantization, pruning, and distillation.
  • Possesses a MS or PhD degree in Computer Science or equivalent industry experience.
  • Experience leading large-scale projects and driving innovation in the field.
  • Strong software engineering skills in Python and ML compiler knowledge.
  • Expertise in high performance kernel implementation and distributed inference.

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