ZipRecruiter

Log In

1

Scientific Machine Learning Jobs in California (NOW HIRING)

Apple

Machine Learning FEA Engineer

Bodega Bay, CA

$142K - $263K/yr

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 ...

Medium

$160 - $190/hr

Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands‑on experience in machine learning and AI; or a Ph.D. in a relevant ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

D. in Computer Science, Data Science, or a related field • Strong programming skills in Python or R • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) • Knowledge of ...

Machina Labs

Machine Learning Engineer

Los Angeles, CA

$160K - $190K/yr

Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands-on experience in machine learning and AI; or a Ph.D. in a relevant ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands-on experience in machine learning and AI; or a Ph.D. in a relevant ...

Spotter

Machine Learning Scientist

Culver City, CA

Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production machine learning models, particularly reinforcement ...

previous pagenext page

Showing results 21-40

All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in California

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in California?

For Scientific Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in California look for?

The top searched job categories for Scientific Machine Learning jobs in California are:

What cities in California are hiring for Scientific Machine Learning jobs?

Cities in California with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning FEA Engineer

Apple

Bodega Bay, CA

$142K - $263K/yr

Full-time

Medical, Dental, Retirement

Re-posted 8 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

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.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

View All Apple Jobs

Apply