5 jobs for "Machine Learning FEA Engineer"

Machine Learning FEA Engineer

At Apple - San Francisco Bay Area

Posted on Oct 8

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Machine Learning FEA Engineer

At Apple - San Francisco Bay Area

Posted on Oct 8

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FEA/AI Methods Engineer

At Apple - San Francisco Bay Area

Posted on Oct 15

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NIKE, Inc. AI & Machine Learning, Innovation Graduate Internship

At NIKE, Inc. - Beaverton

Posted on Sep 30

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Principal Machine Learning Engineer

At Atlassian - Remote / Flexible

Posted on Sep 15

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Apple

Machine Learning FEA Engineer

San Francisco Bay Area, CA$142,300 – $263,300Posted Oct 8, 2026

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Imagine what you can do here! We are committed to pushing the boundaries of innovation and engineering excellence in product designs through machine learning and FEA simulations. We truly believe in the power of predictive simulation to make the impossible possible, transform industries and improve people's lives. As a member of the Product Design FEA team, you will play a pivotal role in developing innovative machine learning technologies and directly impact the success of new iPhone, iPad, Mac, Apple Watch, Vision Pro and many more future products. Come join us and put a dent in the universe!

Description

As a core member of the product design team, you will be responsible for developing and implementing ground-breaking machine learning methods that are based on predictive finite element simulations and important design load cases. The machine learning models will drive rapid design iterations by assessing potential risks and optimizing design trade-offs. You will be fully integrated with the product design team from the earliest stages to engineer ground breaking products.

Preferred Qualifications

Strong expertise in GNNs, CNNs, and transformer-based architectures

Implement and optimize these models for large-scale datasets on scalable ML platforms

Ability to work independently in white space and deal with an incredible fast-paced environment

Excellent cross-functional collaboration and written and verbal communication skills

Ph.D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline

Publications in top journals or conferences

Minimum Qualifications

Strong Expertise in Machine Learning, Deep Learning, and Optimization

Knowledges 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

Passion for creating innovative, high-quality products

Desire to work in a fast-paced environment with passion for creating cutting edge products

M.S. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline along with 3+ years of relevant experience

Pay & 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 $142,300 and $263,300, 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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology

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