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Scientific Machine Learning Jobs (NOW HIRING)

Chabez Tech

Machine Learning Engineer

Portland, OR

... science, Machine Learning, Electrical Engineering, or related field 5+ years of experience in ... machine learning, data science, or AI engineering Strong programming skills in Python (NumPy ...

Chabez Tech

Machine Learning Engineer

Portland, OR · On-site

... computer science, Machine Learning, Electrical Engineering, or related field • 5+ years of ... experience in machine learning, data science, or AI engineering • Strong programming skills in ...

Chabez Tech

Machine Learning Engineer

Portland, OR

... computer science, Machine Learning, Electrical Engineering, or related field • 5+ years of ... experience in machine learning, data science, or AI engineering • Strong programming skills in ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will: Explore: you're open-minded about methods and will ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site

$88K - $121K/yr

This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will: Explore: you're open-minded about methods and will ...

Chabez Tech

Machine Learning Engineer

Portland, OR

... computer science, Machine Learning, Electrical Engineering, or related field • 5+ years of ... experience in machine learning, data science, or AI engineering • Strong programming skills in ...

Rule14

Data Scientist Machine Learning

Santa Monica, CA · On-site

$75K - $100K/yr

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will: Explore: you're open-minded about methods and will ...

Atoms

Machine Learning Engineer

Mountain View, CA · On-site

Required : • Bachelors degree required • Advanced degree (PhD or Master) in Computer Science, Machine Learning, Data Mining, Statistics, or related technical field with preferred 3+ years of ...

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Scientific Machine Learning information

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$13

$31

$52

How much do scientific machine learning jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for scientific machine learning in the United States is $31.48, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $40.14 per hour, depending on experience, location, and employer.

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

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 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.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

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 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.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
More about Scientific Machine Learning jobs
What cities are hiring for Scientific Machine Learning jobs? Cities with the most Scientific Machine Learning job openings:
What states have the most Scientific Machine Learning jobs? States with the most job openings for Scientific Machine Learning jobs include:
What job categories do people searching Scientific Machine Learning jobs look for? The top searched job categories for Scientific Machine Learning jobs are:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in the United States as of June 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $65,473 per year, or $31.5 per hour.
Machine Learning FEA Engineer

Machine Learning FEA Engineer

Apple

San Francisco, CA • On-site

Full-time

Posted 10 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th 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!
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.
Strong Expertise in Machine Learning, Deep Learning, and OptimizationKnowledges of Finite Element Analysis and/or other numerical methods in computational physics and mechanicsProficiency in Python and relevant packages for MLOutstanding communication skillsPassion for creating innovative, high-quality productsDesire to work in a fast-paced environment with passion for creating cutting edge productsM.S. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline along with 3+ years of relevant experience
Strong expertise in GNNs, CNNs, and transformer-based architecturesImplement and optimize these models for large-scale datasets on scalable ML platformsAbility to work independently in white space and deal with an incredible fast-paced environmentExcellent cross-functional collaboration and written and verbal communication skillsPh.D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar disciplinePublications in top journals or conferences

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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