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Physics Based Machine Learning Jobs (NOW HIRING)

Photon

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ... Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ... Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow ...

Quantum Machines

Machine Learning Engineer

Boston, MA · On-site

... based ML services and libraries that integrate with the wider Quantum Machines control stack ... Required : • PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information ...

Applied Physics

Seismologist

Los Angeles, CA

Organize, analyze, and interpret large geophysical sets from ongoing laboratory/field operations and physics-based simulations * Employ physical, statistical, or machine learning-based methods for ...

Applied Physics

Seismologist

Los Angeles, CA · On-site

Organize, analyze, and interpret large geophysical sets from ongoing laboratory/field operations and physics-based simulations * Employ physical, statistical, or machine learning-based methods for ...

Applied Physics

Seismologist

Los Angeles, CA · On-site

Organize, analyze, and interpret large geophysical sets from ongoing laboratory/field operations and physics-based simulations * Employ physical, statistical, or machine learning-based methods for ...

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How much do physics based machine learning jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for physics based machine learning in the United States is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $25.48 per hour, depending on experience, location, and employer.

What is a Physics Based Machine Learning job?

A Physics Based Machine Learning job involves developing machine learning models that incorporate physical laws and domain knowledge to improve predictions and interpretability. Professionals in this field work at the intersection of physics, data science, and artificial intelligence to create models that are more robust, generalizable, and efficient, especially in scientific and engineering applications. Responsibilities often include data analysis, algorithm development, numerical simulations, and integrating physics-based constraints into ML models. These roles are common in industries like climate science, robotics, materials science, and computational physics.

What are the key skills and qualifications needed to thrive in the Physics Based Machine Learning position, and why are they important?

To thrive in Physics Based Machine Learning, you need advanced knowledge of physics, strong programming skills (Python, MATLAB, or C++), and a deep understanding of machine learning and statistical modeling, typically supported by a master's or PhD in physics, engineering, or a related field. Familiarity with simulation software, scientific computing libraries (such as TensorFlow, PyTorch, NumPy), and version control systems is essential. Strong problem-solving ability, effective communication, and cross-disciplinary collaboration skills set outstanding candidates apart. These competencies are crucial for designing robust, real-world models that integrate physical principles with data-driven techniques to solve complex problems.

What types of projects or problems does a Physics Based Machine Learning professional typically work on?

Physics Based Machine Learning professionals often work on projects that involve applying machine learning techniques to physical systems, such as improving simulations in engineering, optimizing energy systems, or accelerating scientific research through data-driven modeling. Daily tasks might include developing algorithms that incorporate physical laws, analyzing simulation data, and collaborating with experts from engineering, data science, or research teams. The role can involve both theoretical and hands-on work, often requiring iterative testing and validation. This environment provides opportunities to tackle cutting-edge challenges, contribute to innovation, and potentially lead to career paths in research, product development, or advanced analytics.
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Physics Based Machine Learning jobs near you
Infographic showing various Physics Based Machine Learning job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 61% Full Time, and 37% Part Time. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $41,731 per year, or $20.1 per hour.
Physicist/Scientist Machine Learning

Physicist/Scientist Machine Learning

Applied Materials

Santa Clara, CA • On-site

$138K - $190K/yr

Full-time

Posted 18 days ago

Applied Materials rating

8.6

Company rating: 8.6 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

24th of 515 rated manufacturers

Job description

Who We Are
Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips - the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world - like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.
What We Offer
Salary:
$138,000.00 - $190,000.00
Location:
Santa Clara,CA
You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.
At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.
We are seeking a highly motivated MS or PhD-level scientist or engineer to develop and apply machine learning-based models using data generated from multi-dimensional, high-performance computing (HPC) simulations. The successful candidate will work at the intersection of physics-based modeling, large-scale simulation, and modern AI/ML methods to accelerate product developing in the fast-paced semiconductor equipment industry. Focus will be on developing ML models based on plasma and electromagnetic simulations.
This role is ideal for candidates with strong domain knowledge in engineering or physical sciences and hands-on experience translating complex simulation data into robust, predictive machine learning models.
Required Qualifications
  • MS or PhD in Engineering (e.g., Chemical, Electrical, Mechanical, Aerospace, Nuclear, Materials), Science (e.g., Physics, Chemistry), or Computer Science
  • Significant experience developing machine learning or deep learning models using data from multi-dimensional numerical simulations (e.g., PDE-based solvers, particle-based simulations, multiphysics models)
  • Strong background in Python-based scientific computing and ML workflows
  • Demonstrated experience with PyTorch or equivalent deep learning frameworks
  • Solid understanding of:
    • Data preprocessing and feature engineering for large, high-dimensional datasets
    • Model training, validation, and performance evaluation
    • Numerical methods and/or physics-based modeling concepts

Preferred Qualifications
  • Experience with NVIDIA Physics NeMo, NVIDIA Modulus, or related physics-informed or simulation-driven ML libraries
  • Familiarity with GPU-accelerated computing, CUDA-aware workflows, and HPC environments
  • Exposure to physics-informed machine learning (PIML), surrogate modeling, reduced-order modeling, or operator learning
  • Publications or demonstrated research contributions in ML for physical systems or related fields

Key Responsibilities
  • Develop and train machine learning and deep learning models using data from large-scale, multi-dimensional HPC simulations
  • Collaborate with domain experts to incorporate physical constraints, scientific insight, and prior knowledge into ML model design
  • Design workflows for data ingestion, curation, and analysis of high-volume simulation outputs
  • Evaluate model accuracy, generalization, and robustness across a wide range of operating conditions
  • Optimize models for performance, scalability, and deployment on GPU-accelerated platforms
  • Contribute to internal software tools, modeling frameworks, and best practices

Additional Information
Time Type:
Full time
Employee Type:
New College Grad
Travel:
Yes, 10% of the Time
Relocation Eligible:
Yes
The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.
For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.

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About Applied Materials

Sourced by ZipRecruiter

Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We're the brain (and the brawn) behind every new technology development--whether it's building semiconductor chips for smartphones and computers, or the underpinnings for robotics, AI and even smart TV display screens. With 27,000 employees in 19 countries, we offer an exciting place to grow and learn alongside some of the best people you'll ever meet. We take deep pride in our Culture of Inclusion, and we celebrate the diverse backgrounds, perspectives and experiences that help us build stronger, more resilient teams. Join us as we innovate to Make Possible a Better Future!

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1967

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