Apple
Machine Learning FEA Engineer
$142K–$278K
San Francisco Bay Area, California +1 · Full-time · Posted Oct 5, 2026
- Location
- San Francisco Bay Area, California
Culver City, California - Experience
- 3+ years of relevant experience.
- Education
- M.S. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline.
About the job
Develop machine learning methods based on predictive finite element simulations to assess design risks and optimize trade-offs for Apple products.
What you'll do
- Develop and implement machine learning methods based on predictive finite element simulations and design load cases.
- Build models that enable rapid design iterations by assessing risks and optimizing design trade-offs.
- Work with the product design team from early product-development stages.
What they ask for
- Strong expertise in machine learning, deep learning, and optimization.
- Knowledge of Finite Element Analysis and/or numerical methods in computational physics and mechanics.
- Proficiency in Python and relevant ML packages; outstanding communication skills.
- M.S. in a relevant discipline and 3+ years of relevant experience.
Nice to have
- Expertise in GNNs, CNNs, and transformer-based architectures; experience implementing and optimizing models for large-scale datasets on scalable ML platforms.
- Ph.D. in a relevant discipline or publications in top journals or conferences.
Pay
$142,300 and $263,300 USD (base salary); $150,400 and $277,600 USD (base salary)
Tools
Python, GNNs, CNNs
AI focus
Develop ML models using predictive FEA simulations to support product design risk assessment and optimization.
Model-written summary · the original posting is authoritative