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Ai For Materials Jobs (NOW HIRING)

Amat

AI Materials Research Engineer

Santa Clara, CA

$170K - $234K/yr

Develop AI/ML models for: * Materials property prediction * Materials screening and optimization * Process-performance modeling * Generative materials design * Apply computational ...

SES

Technical Product Manager

Woburn, MA · On-site +1

$200K - $225K/yr

This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage ...

AuraOne

$100 - $125/hr

Materials Science Domain Expert -- AI Evaluation (Remote, Bay Area) is a remote review track for evaluating AI outputs across materials science reasoning, calculations, and research workflows.

New

TripleTen

AI for Smart Work, AI for Sales, AI for L&D, AI for Marketing, and AI for Teachers. We recruit ... Create educational content, assessments, and project-based learning materials * Design practical ...

TripleTen

Authors design and write the learning materials for AI for Managers - building frameworks, case studies, and structured content tailored to non-technical, managerial audiences. They bring 7+ years in ...

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Ai For Materials information

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$38K

$100.7K

$158K

How much do ai for materials jobs pay per year?

As of Sep 7, 2026, the average yearly pay for ai for materials in the United States is $100,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What is AI for Materials?

AI for Materials refers to the use of artificial intelligence and machine learning techniques to accelerate the discovery, design, and optimization of new materials. By analyzing large datasets and predicting properties, AI helps scientists identify promising materials for applications such as energy, electronics, and manufacturing. This approach significantly reduces the time and cost associated with traditional experimental methods, making materials research more efficient and innovative.

What are some typical challenges faced by professionals working in AI for Materials Science, and how can these be addressed?

Professionals in AI for Materials Science often encounter challenges such as limited high-quality data, integrating domain knowledge with machine learning models, and ensuring model interpretability for scientific insights. Collaborating closely with materials scientists and data engineers helps bridge knowledge gaps and improve dataset quality. Additionally, staying updated with the latest AI techniques and actively participating in interdisciplinary teams can enhance problem-solving and foster innovation in this rapidly evolving field.

What are the key skills and qualifications needed to thrive as an AI for Materials specialist, and why are they important?

To thrive as an AI for Materials Specialist, you need a solid background in materials science, data analysis, and proficiency in machine learning, often supported by an advanced degree in materials engineering, chemistry, or computer science. Familiarity with programming languages like Python, machine learning frameworks (e.g., TensorFlow, PyTorch), and materials databases is typically required. Strong problem-solving skills, collaboration, and effective communication are vital soft skills for interpreting complex data and working with interdisciplinary teams. These competencies enable the effective application of AI to accelerate materials discovery and innovation in research or industrial settings.

What is the difference between Ai For Materials vs Materials Scientist?

AspectAi For MaterialsMaterials Scientist
Required CredentialsTypically requires knowledge of AI, machine learning, and materials science fundamentalsRequires a degree in materials science, chemistry, or related fields, often with advanced degrees
Work EnvironmentPrimarily in tech labs, R&D centers, or software development teamsLaboratories, research institutions, or industrial settings
Industry UsageUsed in materials discovery, simulation, and optimization through AI toolsFocuses on experimental research, characterization, and development of materials

While Ai For Materials involves applying AI techniques to materials research, Materials Scientists focus on experimental and theoretical study of materials. Both roles often collaborate but differ in their core skills and work environments.

Infographic showing various Ai For Materials job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $100,738 per year, or $48.4 per hour.

AI Materials Research Engineer

Applied Materials

Santa Clara, CA • On-site

$170K - $234K/yr

Full-time

Posted 11 days ago

Applied Materials rating

8.7

Company rating: 8.7 out of 10

Based on 58 frontline employees who took The Breakroom Quiz

15th of 546 rated manufacturers

Job description

Who We Are
Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world's technology.
What We Offer
Salary:
$170,000.00 - $234,000.00
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.
Role Summary
Applied Materials is seeking an AI MaterialsResearch Engineer to accelerate semiconductor materials discovery using Scientific AI, Computational MaterialsScience, and Machine Learning. The role combines materials science expertise with AI/ML, simulation, and data-driven modeling to develop next-generation materials and process innovations. Based on related internal Materials AI role descriptions.
Key Responsibilities
  • Develop AI/ML models for:
    • Materials property prediction
    • Materials screening and optimization
    • Process-performance modeling
    • Generative materials design
  • Apply computational materialsmethodologies including:
    • Density Functional Theory (DFT)
    • Molecular Dynamics (MD)
    • Kinetic Monte Carlo (kMC)
    • Phase-field and Monte Carlo simulations
  • Build AI surrogate models to accelerate simulation-driven research.
  • Create materials informatics pipelines integrating:
    • Experimental data
    • Characterization results
    • Simulation outputs
    • Scientific literature
  • Develop AI copilots and agentic workflows for:
    • Literature review
    • Hypothesis generation
    • Experiment planning
    • Simulation orchestration
  • Collaborate with materials scientists, process engineers, and AI teams to deliver Scientific AI solutions.
Required Qualifications
  • MS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or related field.
  • 2-5 years of experience in Computational Materials Science, Materials Informatics, Scientific ML, or AI for scientific applications.
  • Strong Python programming and ML experience (PyTorch, TensorFlow, Scikit-Learn).
  • Experience with one or more computational methods:
    • DFT
    • MD
    • kMC
    • Phase-Field Modeling
  • Strong understanding of:
    • Crystal structures
    • Thermodynamics
    • Kinetics
    • Defect physics
    • Semiconductor materials
Preferred Qualifications
  • Experience with simulation platforms such as VASP, Quantum Espresso, CP2K, LAMMPS, or GROMACS.
  • Experience with Materials Project, OQMD, NOMAD, or similar databases.
  • Familiarity with:
    • Graph Neural Networks (GNNs)
    • Materials Foundation Models
    • Physics-Informed ML
    • Generative AI for materials design
  • Experience using cloud/HPC environments for large-scale model training and simulations.

Additional Information
Time Type:
Full time
Employee Type:
Assignee / Regular
Travel:
Not Specified
Relocation Eligible:
No
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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