TN Visa Machine Learning Engineer Jobs
Machine Learning Engineer roles qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst category, which covers ML-focused positions requiring a computer science, mathematics, or engineering degree. Canadian citizens can secure TN status at the port of entry with no cap or lottery. Mexican citizens apply through a U.S. consulate.
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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 Machine Learning Engineer
Align your credentials to the Computer Systems Analyst category
TN visa status for ML engineers is adjudicated under Computer Systems Analyst, not a standalone ML category. Your degree in computer science, mathematics, statistics, or engineering must be documented and translated if issued outside the U.S. or Canada.
Target employers experienced with visa sponsorship
Companies experienced with work visa sponsorship understand the employer support letter requirements and won't delay your start date. Migrate Mate identifies employers with recent visa filings, showing which companies regularly hire for technical roles like Machine Learning Engineer across tech, finance, and healthcare.
Search TN-sponsoring ML roles through Migrate Mate
Filter by TN visa sponsorship and the Machine Learning Engineer title to surface employers actively hiring for this category. Migrate Mate surfaces verified sponsorship history so you're not guessing which companies will actually file.
Get your employer letter drafted before negotiating your start date
Canadian citizens can activate TN status at the border the same day, but only with a compliant employer support letter. The letter must name the specific ML role, confirm the Computer Systems Analyst classification, and state the duration and wages.
Clarify your job duties if your title sounds more research than engineering
Titles like Research Scientist or AI Researcher can raise questions at the port of entry. If your role involves applied ML systems rather than pure research, your employer letter should describe deliverables, tools, and systems responsibilities to support the Computer Systems Analyst classification.
Understand Mexican citizens face a separate consular process
Unlike Canadians, Mexican TN applicants must schedule a consular interview in Mexico and receive visa stamp issuance before entering the U.S. Plan for a consulate appointment timeline and confirm your employer can accommodate the additional processing window.
Machine Learning Engineer TN Visa: Frequently Asked Questions
Does a Machine Learning Engineer role qualify for TN visa sponsorship?
Yes, Machine Learning Engineer positions qualify under the USMCA's Computer Systems Analyst category, which covers roles requiring theoretical and practical application of computer systems. Your offer letter and job duties must reflect systems analysis and implementation work. Roles framed primarily as academic research can face more scrutiny at adjudication.
How does TN compare to H-1B for Machine Learning Engineers?
TN has no annual lottery, no cap for Canadian citizens, and can be activated at a Canadian port of entry the same day with the right documentation. H-1B visa requires a lottery selection, an April registration window, and an October 1 start date at earliest. For ML engineers with Canadian or Mexican citizenship, TN is a faster and more predictable path to authorized employment.
What documentation does my employer need to provide for my TN application?
Your employer must provide a support letter on company letterhead that names your specific ML role, confirms the Computer Systems Analyst USMCA classification, describes your job duties, states the offered wage, and specifies the employment duration. Canadian applicants present this letter directly to CBP at the port of entry. Mexican applicants include it in their consular application package.
Where can I find Machine Learning Engineer jobs that offer TN visa sponsorship?
Migrate Mate is built specifically for TN visa job seekers and lets you filter by visa type and job title to find employers actively sponsoring Canadian and Mexican professionals. This is more targeted than searching general job boards, where sponsorship willingness is often unclear or unlisted in the posting.
Can I switch Machine Learning Engineer employers while on TN status?
Yes, but TN status is employer-specific, so you cannot start work with a new employer on your existing TN authorization. Your new employer must obtain a fresh TN approval before your first day, either through a CBP port of entry (for Canadians) or a USCIS petition filed in advance. Plan your transition timeline to avoid a gap in authorized employment.