TN Visa Machine Learning Jobs
Machine Learning roles qualify for TN visa sponsorship under the Engineer or Computer Systems Analyst categories, depending on how the position is structured. Canadian citizens can secure TN status at the border with no cap or lottery. Mexican citizens require a consular appointment. A qualifying bachelor's degree in a technical field is required.
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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 in Machine Learning
Match your degree to the TN category
TN visa approval for Machine Learning roles depends on whether your employer files under Engineer or Computer Systems Analyst. Your degree field must align with whichever category the job description supports. A mismatch is the most common denial trigger.
Request an offer letter that names TN
Your offer letter must explicitly state the TN category, your specific duties, and the employment period. Employers who routinely sponsor H-1B visa often need prompting to format a TN support letter correctly since the requirements differ significantly.
Target employers with active ML research teams
Companies running dedicated Machine Learning infrastructure are more likely to understand work visa sponsorship processes. Look for job postings from employers with recent visa filings, research publications, or roles requiring specialized technical degrees, which signal prior experience navigating work authorization requirements.
Prepare your credential documents before applying
Gather your degree transcripts, any credential evaluations, and a detailed job description before you start applications. Canadian citizens presenting at the port of entry need everything ready on the spot since CBSA reviews documentation immediately.
Use Migrate Mate to filter for TN-ready employers
Searching broadly wastes time on employers unfamiliar with TN visa mechanics. Migrate Mate lets you filter Machine Learning roles by companies that have sponsored TN or similar work visas, so you focus on employers who won't need education on the process.
Clarify the job title before the offer stage
Job titles in Machine Learning vary widely. 'AI Engineer,' 'Data Scientist,' and 'ML Researcher' can map to different TN categories. Confirm with your prospective employer which title will appear on the support letter before any filing or border appointment.
Machine Learning TN Visa: Frequently Asked Questions
Does a Machine Learning job qualify for a TN visa?
Machine Learning roles can qualify under the Engineer or Computer Systems Analyst TN category, depending on how the job duties are framed and your degree field. The role must require at least a bachelor's degree in a directly related technical discipline. A generic 'technology' degree without clear alignment to the job description can cause problems at the border or consulate.
How does TN compare to H-1B for Machine Learning professionals?
TN is often faster and more predictable for Machine Learning roles than H-1B. Canadians can get TN status at the port of entry in a single day, with no lottery and no cap. H-1B requires an annual lottery with roughly a 25 percent selection rate and a six-month wait. Mexican nationals face a TN cap of 5,500 per year, so H-1B may be worth pursuing as a parallel path if you anticipate long-term U.S. employment.
Can a Canadian Machine Learning professional get TN status without a job offer already in hand?
No. TN status requires a concrete job offer from a specific U.S. employer before you can apply. You cannot get TN status speculatively or as a job-search visa. The offer letter must describe your duties, confirm the TN category, and state the employment period. Only after that letter exists can a Canadian present at the border or a Mexican schedule a consular appointment.
Where can I find Machine Learning jobs where the employer is already familiar with TN sponsorship?
Migrate Mate is built specifically for this search. It surfaces Machine Learning roles at companies with documented work visa sponsorship history, so you avoid spending time on employers who will decline or delay because they don't understand TN mechanics. Searching with that filter significantly shortens the time between application and offer.
What happens if my TN visa is denied at the border for a Machine Learning role?
If CBSA or CBP denies your TN application, you can reapply at a different port of entry or consulate once you've addressed the reason for denial, which is typically a documentation gap or a degree-to-job mismatch. There is no mandatory waiting period for reapplication. You should revise your support letter and, if the category was the issue, confirm with your employer that the job description supports the intended TN classification before reapplying.