TN Visa AI Researcher Jobs
AI Researcher roles qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst and Scientific Technician categories, depending on how the position is defined. Canadian citizens can enter at the border with a qualifying job offer. Mexican nationals apply at a U.S. consulate. A relevant degree in computer science, mathematics, or a related field is required.
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Get Access To All JobsWho 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.
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.
Role Summary
Applied Materials is seeking an AI Materials Research Engineer to accelerate semiconductor materials discovery using Scientific AI, Computational Materials Science, 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 materials methodologies 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.
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.
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.
Role Summary
Applied Materials is seeking an AI Materials Research Engineer to accelerate semiconductor materials discovery using Scientific AI, Computational Materials Science, 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 materials methodologies 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.
See all TN Visa AI Researcher Jobs
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Get Access To All JobsTips for Finding TN Visa Sponsorship in AI Researcher
Frame your degree for TN eligibility
TN visa officers assess whether your credential matches the job's specialty occupation. A degree in machine learning or statistics maps more cleanly than a general engineering degree, so reframe your transcripts and credential evaluations to highlight AI-relevant coursework and research focus.
Target employers with established TN programs
Research companies that have recent visa filings for Computer Systems Analyst or related roles. Employers experienced with visa sponsorship processes move faster and are more likely to support work visa applications, including TN sponsorship through the standard port-of-entry or consulate procedures.
Clarify your role title before the offer stage
AI Researcher can be classified differently depending on the duties listed. Before signing an offer, confirm with the employer that your job description maps to a USMCA-recognized category, not a role that only fits H-1B visa petition-based classification.
Use Migrate Mate to surface TN-ready employers
Migrate Mate filters AI Researcher roles by TN visa sponsorship history, saving you from applying to companies unfamiliar with the process. Search by role and location to find employers already equipped to support your entry.
Prepare a support letter that mirrors USMCA language
Your employer's support letter must tie your duties to a recognized TN category using standard professional terminology. Generic offer letters citing 'AI research' without connecting to a defined professional category are a common reason CBP officers ask additional questions at the border.
Understand Mexican nationals need consular appointment timing
Mexican professionals can't use the expedited Canadian land-border process and must schedule a consular interview. Factor in consulate wait times when negotiating your start date with the employer, since delays of several weeks are common at high-volume posts.
AI Researcher TN Visa: Frequently Asked Questions
Does an AI Researcher role qualify for TN visa sponsorship?
It depends on how the role is defined. TN visa eligibility for AI Researchers typically falls under the Computer Systems Analyst or Scientific Technician categories recognized under USMCA. The job duties and your degree must align with a qualifying category. Roles focused on pure theoretical research without an applied technical component can be harder to classify and may require a more detailed employer support letter.
How does TN visa sponsorship compare to H-1B for AI Researcher positions?
TN has no lottery and no annual cap for Canadian citizens, so you can start without waiting for a selection cycle. H-1B is subject to an annual lottery with limited slots, meaning most applicants wait at least a year for a chance at approval. TN status is also employer-specific and role-specific, so changing jobs requires new documentation, similar to H-1B, but the initial entry process is significantly faster for Canadians.
Can I switch AI Researcher roles while on TN status?
Yes, but you can't start working for a new employer under your existing TN. You'll need a new TN approval tied to the new employer and position before your first day. Canadian professionals can often handle this at a port of entry with updated documentation. Mexican nationals must return to a consulate. Build transition time into your job search timeline so you're not left in a gap.
How do I find AI Researcher jobs where the employer already understands TN sponsorship?
Migrate Mate is built specifically for this. You can search AI Researcher roles filtered by TN visa sponsorship history, so you're targeting companies that have already navigated the process. This cuts out the back-and-forth of educating employers about TN requirements and speeds up the time from offer to start date.
What degree does a Canadian or Mexican AI Researcher need for TN eligibility?
USCIS and CBP expect a bachelor's degree or higher in a field directly relevant to the role, typically computer science, mathematics, statistics, or a closely related discipline. A general business or social science degree, even paired with extensive AI experience, will not satisfy the requirement on its own. Canadian three-year bachelor's degrees are generally accepted as equivalent to U.S. four-year degrees for TN purposes.