
Machine Learning FEA Engineer
Required skills
- Machine Learning
- Deep Learning
- Optimization
- Finite Element Analysis
- numerical methods
- computational physics
- mechanics
- Python
- ML packages
Nice to have
- GNNs
- CNNs
- transformer-based architectures
- large-scale datasets
- scalable ML platforms
Role summary
We are seeking a Machine Learning FEA Engineer to develop and implement innovative machine learning methods based on predictive finite element simulations. This role will drive rapid design iterations by assessing risks and optimizing design trade-offs for new products like iPhone, iPad, Mac, and Apple Watch. The ideal candidate will have strong expertise in Machine Learning, Deep Learning, Optimization, Finite Element Analysis, and Python, with 3+ years of relevant experience. Preferred qualifications include expertise in GNNs, CNNs, and transformer-based architectures, and experience with scalable ML platforms.
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.
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
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
Sample Apple interview questions
- 1
Design a typeahead box for a search engine
system designmedium - 2
Design a rate limiter
system designmedium - 3
Architect a key-value store for distributed systems.
system designmedium - 4
Design a system to schedule jobs in a distributed environment
system designmedium - 5
What is an API and how does it work?
technicalmedium
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