Machine Learning FEA Engineer

Apple Inc

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Quick summary

Work type
On-site
Location
San Francisco, CA
Salary
$142,300–$263,300 / yr
Posted
21 days ago
Freshness
Confirmed live today

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $216k
This role $203k
$128k $278k
below market most similar roles pay here above market

This role pays less than 59% of similar roles. Most pay $185,231–$246,150 — the blue band above. At the midpoint, this role pays about $203k versus about $216k 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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Machine Learning FEA Engineer

As a Machine Learning FEA Engineer on the Product Design FEA team, you will develop and implement groundbreaking machine learning methods based on predictive finite element simulations and important design load cases. You will work closely with the product design team from the earliest stages to engineer new products, including the iPhone, iPad, Mac, and Apple Watch. Your daily responsibilities involve creating models that drive rapid design iterations by assessing potential risks and optimizing design trade-offs. You must possess expertise in machine learning, deep learning, optimization, and finite element analysis or other numerical methods in computational physics and mechanics. Required technical skills include proficiency in Python and relevant ML packages, with preferred experience in GNNs, CNNs, and transformer-based architectures for large-scale datasets on scalable ML platforms.

What you'll do

  • Develop and implement machine learning methods based on predictive finite element simulations.
  • Assess potential design risks and optimize design trade-offs using ML models.
  • Drive rapid design iterations for new hardware products like iPhone and Mac.
  • Integrate with the product design team from the earliest stages of engineering.
  • Implement and optimize GNNs, CNNs, and transformer-based architectures for large-scale datasets.
  • Deploy models on scalable machine learning platforms.
  • Apply numerical methods in computational physics and mechanics to product design.

What we're looking for

  • M.S. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline.
  • 3+ years of relevant experience.
  • Strong expertise in Machine Learning, Deep Learning, and Optimization.
  • Knowledge of Finite Element Analysis and/or other numerical methods in computational physics and mechanics.
  • Proficiency in Python and relevant packages for ML.
  • Outstanding communication skills and a passion for creating innovative, high-quality products.
  • Ph.D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline (preferred).
  • Strong expertise in GNNs, CNNs, and transformer-based architectures (preferred).

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