TN Visa ML Engineer Jobs
ML Engineer roles qualify for TN visa sponsorship under USMCA's Computer Systems Analyst category when the position requires applying machine learning methods to analyze and solve systems problems. Canadian citizens can enter at the port of entry without a cap. Mexican citizens go through U.S. consular processing with a limited annual allocation.
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Get Access To All JobsINTRODUCTION
The Care Health and Reasoning Machines (CHARM) lab led by Dr. Jeremy C. Weiss at the National Library of Medicine seeks to hire a postdoctoral fellow at the intersection(s) of the following research areas: longitudinal machine learning, multi-modal analysis, clinical informatics, and population health.
About the position
The National Library of Medicine (NLM) is one of the 27 institutes at the National Institutes of Health (NIH). NLM is the world’s largest biomedical library and a leader in research, development, and training in biomedical informatics and health information technology. The Division of Intramural Research (DIR) within NLM has two primary research areas: computational health research and computational biology.
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In computational health research, our efforts center on natural language processing (NLP), clinical image analysis, biomedical ontologies, information modeling, and clinical data analytics.
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In computational biology, we emphasize transcriptional regulation, chromatin and network biology, structural and functional analysis, sequence statistics, and evolutionary genomics.
The CHARM lab is investigating methods that learn from longitudinal, textual and tabular data present in health data that (1) are predictive forecasters, and (2) preserve interrogable properties. The research will address the trustworthiness of electronic health records and complementary biomedical data for clinical decision making. Relevant experience includes expertise in representation learning, longitudinal data, annotation, curation, large-language models, and multi-modal learning, with applications in health domains. Relevant programming experience includes pytorch/huggingface/sklearn and R/tidyverse.
Recent relevant publications:
- Wang J, Weiss JC. A Large-Language Model Framework for Relative Timeline Extraction from PubMed Case Reports. American Medical Informatics Association Informatics Summit. Pittsburgh, 2025.
- Frattallone-Llado G, Kim J, Cheng C, Salazar D, Edakalavan S, Weiss JC. Using Multimodal Data to Improve Precision of Inpatient Event Timelines. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2024.
- Noroozizadeh S, Weiss JC, and George Chen. “Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression.” Machine Learning for Health. PMLR. 2023.
Position Overview: This is a full-time postdoctoral fellow position. The initial appointment will be for one year, and is renewable on a yearly basis, with extensions up to 5 years total. The NIH offers a competitive stipend (based on postdoctoral experience, see stipend tables) and a stipend supplement for comprehensive health insurance. The NIH is dedicated to the continued education and career development of all its research staff. Candidates are subject to a background investigation. Explore additional information about NIH postdoctoral fellowships.
What you'll need to apply
Applicants should submit the following materials to Jeremy Weiss, MD, PhD at jeremy.weiss@nih.gov:
- Updated CV
- Cover letter with a short research statement and preferred starting date
- Link(s) to published artifacts (packages, github repositories, etc), and
- Contact information for 3 references (please include the full name with titles, institute, email address and phone number of each reference)
Prospective candidates should include "Postdoc Position Inquiry" and their last name in the email subject line.
Application Deadline: Applications will be accepted and reviewed on a rolling basis until the position is filled.
Contact name: Dr. Jeremy Weiss
Contact email: jeremy.weiss@nih.gov
QUALIFICATIONS
- PhD and/or MD, or equivalent in related subject areas, including machine learning, computer science, medicine, bioinformatics, biomedical informatics and statistics/biostatistics
- Clinical Machine Learning: Programming experience in python, pytorch; R, Julia, and/or C++
- Publishing experience with peer-reviewed journals or conferences in the above areas
INTRODUCTION
The Care Health and Reasoning Machines (CHARM) lab led by Dr. Jeremy C. Weiss at the National Library of Medicine seeks to hire a postdoctoral fellow at the intersection(s) of the following research areas: longitudinal machine learning, multi-modal analysis, clinical informatics, and population health.
About the position
The National Library of Medicine (NLM) is one of the 27 institutes at the National Institutes of Health (NIH). NLM is the world’s largest biomedical library and a leader in research, development, and training in biomedical informatics and health information technology. The Division of Intramural Research (DIR) within NLM has two primary research areas: computational health research and computational biology.
-
In computational health research, our efforts center on natural language processing (NLP), clinical image analysis, biomedical ontologies, information modeling, and clinical data analytics.
-
In computational biology, we emphasize transcriptional regulation, chromatin and network biology, structural and functional analysis, sequence statistics, and evolutionary genomics.
The CHARM lab is investigating methods that learn from longitudinal, textual and tabular data present in health data that (1) are predictive forecasters, and (2) preserve interrogable properties. The research will address the trustworthiness of electronic health records and complementary biomedical data for clinical decision making. Relevant experience includes expertise in representation learning, longitudinal data, annotation, curation, large-language models, and multi-modal learning, with applications in health domains. Relevant programming experience includes pytorch/huggingface/sklearn and R/tidyverse.
Recent relevant publications:
- Wang J, Weiss JC. A Large-Language Model Framework for Relative Timeline Extraction from PubMed Case Reports. American Medical Informatics Association Informatics Summit. Pittsburgh, 2025.
- Frattallone-Llado G, Kim J, Cheng C, Salazar D, Edakalavan S, Weiss JC. Using Multimodal Data to Improve Precision of Inpatient Event Timelines. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2024.
- Noroozizadeh S, Weiss JC, and George Chen. “Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression.” Machine Learning for Health. PMLR. 2023.
Position Overview: This is a full-time postdoctoral fellow position. The initial appointment will be for one year, and is renewable on a yearly basis, with extensions up to 5 years total. The NIH offers a competitive stipend (based on postdoctoral experience, see stipend tables) and a stipend supplement for comprehensive health insurance. The NIH is dedicated to the continued education and career development of all its research staff. Candidates are subject to a background investigation. Explore additional information about NIH postdoctoral fellowships.
What you'll need to apply
Applicants should submit the following materials to Jeremy Weiss, MD, PhD at jeremy.weiss@nih.gov:
- Updated CV
- Cover letter with a short research statement and preferred starting date
- Link(s) to published artifacts (packages, github repositories, etc), and
- Contact information for 3 references (please include the full name with titles, institute, email address and phone number of each reference)
Prospective candidates should include "Postdoc Position Inquiry" and their last name in the email subject line.
Application Deadline: Applications will be accepted and reviewed on a rolling basis until the position is filled.
Contact name: Dr. Jeremy Weiss
Contact email: jeremy.weiss@nih.gov
QUALIFICATIONS
- PhD and/or MD, or equivalent in related subject areas, including machine learning, computer science, medicine, bioinformatics, biomedical informatics and statistics/biostatistics
- Clinical Machine Learning: Programming experience in python, pytorch; R, Julia, and/or C++
- Publishing experience with peer-reviewed journals or conferences in the above areas
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Get Access To All JobsTips for Finding TN Visa Sponsorship as a ML Engineer
Align your credentials to Computer Systems Analyst
TN visa approval for ML Engineer roles hinges on classification under Computer Systems Analyst. Your degree in computer science, mathematics, or a related field must map directly to that category. A mismatch in classification is the most common denial trigger for ML candidates.
Target employers with documented ML infrastructure
Seek out companies running production ML systems, not just data science experiments. Employers who already deploy model pipelines are more likely to frame your role in systems terms, which strengthens the specialty occupation argument CBP or a consular officer will scrutinize.
Request a detailed support letter from your employer
Your employer's support letter must describe your specific duties in systems analysis terms, not just 'train models' or 'build algorithms.' Push for language that connects ML engineering tasks to systems design, deployment architecture, and technical problem-solving for the organization.
Prepare for Canadians entering at the port of entry
Canadian citizens apply directly at a land border or airport port of entry without scheduling a consular appointment. Bring your job offer letter, credential documents, and employer support letter. CBP officers adjudicate on the spot, so a disorganized packet can cause delays or denial.
Search for sponsoring employers through Migrate Mate
Filtering job openings by TN visa compatibility saves time you'd otherwise spend cold-contacting employers who won't sponsor. Migrate Mate surfaces ML Engineer roles from employers already open to TN candidates, so you spend less effort on outreach that goes nowhere.
Verify the role qualifies before accepting an offer
Not every ML Engineer job title maps cleanly to a TN-eligible occupation. Before signing, confirm with the employer that the position's core duties center on computer systems analysis. Roles focused primarily on research or data labeling carry a higher risk of CBP pushback at entry.
ML Engineer TN Visa: Frequently Asked Questions
Does ML Engineer qualify as a TN visa occupation?
ML Engineer isn't a listed TN occupation by title, but the role typically qualifies under the Computer Systems Analyst category. The job duties must center on analyzing, designing, and implementing computer systems solutions using machine learning methods. If the role is primarily research-oriented or lacks a clear systems component, a CBP officer may decline to classify it as TN-eligible.
How does TN compare to H-1B for ML Engineer roles?
TN has no annual lottery and no cap for Canadian citizens, so you can start working as soon as your application is approved, often the same day at the port of entry. H-1B visa requires winning a lottery with roughly a 25% selection rate and waiting until October 1 to begin work. For Mexican citizens, TN has a limited annual allocation, but consular processing is still faster than H-1B timelines.
Where can I find ML Engineer jobs that offer TN visa sponsorship?
Migrate Mate is built specifically for Canadian and Mexican professionals seeking TN-eligible roles. You can search ML Engineer positions filtered by TN visa compatibility, which removes the guesswork of figuring out which employers will support a TN filing. Most general job boards don't filter by visa type, so you end up spending time on applications that go nowhere for immigration reasons.
Can a Canadian ML Engineer apply for TN at the border without an attorney?
Yes. Canadian citizens don't need to file a petition with USCIS in advance. You present your application package directly to a CBP officer at a port of entry. That package must include a formal job offer letter, your employer's support letter describing the systems analyst duties, and evidence of your qualifying degree. Incomplete or poorly framed documentation is the main reason for same-day denials.
What happens to my TN status if my ML Engineer role shifts toward pure research?
TN status under Computer Systems Analyst is tied to the duties your employer described when you entered. If your role evolves significantly, such as moving from systems deployment to academic-style research, you may no longer meet the classification criteria. Your employer should issue an amended support letter and you should discuss whether a new TN entry or an alternative visa category is appropriate before your next renewal or travel.