TN Visa Machine Learning Manager Jobs
Machine Learning Manager roles qualify for TN visa sponsorship under USMCA's Computer Systems Analyst category, provided your job duties center on systems design and analysis rather than pure research. Canadian citizens can apply at the border; Mexican citizens go through consular processing. Employers file no lottery petition, making offers faster to execute than H-1B visa.
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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 Manager
Frame your credentials around systems analysis
TN visa classification for ML Manager roles hinges on Computer Systems Analyst duties, not research. Your resume and support letter must emphasize system design, integration, and deployment work over academic or experimental ML activities.
Verify your degree maps to the category
CBP officers scrutinize whether your computer science, engineering, or applied math degree aligns with the Computer Systems Analyst classification. A degree in an unrelated field without clear course equivalency creates denial risk at the port of entry.
Target employers with active USMCA filing history
Prioritize companies with recent visa filing experience. Employers who have sponsored work visas before typically have streamlined internal processes and understand visa sponsorship requirements, so they're less likely to delay your offer due to legal review complications.
Get your job offer letter TN-specific before crossing
Canadian citizens present their TN package directly to CBP at the border, so your employer's support letter must name the USMCA category, describe qualifying duties, and state the employment period. A vague letter causes on-the-spot denial with no appeal.
Search for TN-ready ML Manager roles using Migrate Mate
Filter specifically for Machine Learning Manager positions where employers have indicated TN visa sponsorship. Migrate Mate surfaces roles by visa type so you're not cold-applying to companies unfamiliar with USMCA professional classifications.
Plan Mexican consular processing timelines into your start date
Mexican nationals must schedule a consular interview, which adds weeks to your timeline. Build at least 60 days between your signed offer and your target start date to account for appointment availability and document preparation.
Machine Learning Manager TN Visa: Frequently Asked Questions
Does a Machine Learning Manager role qualify for TN visa status?
Yes, if your duties align with the Computer Systems Analyst classification under USMCA. CBP evaluates the actual job responsibilities, not the title. Your role must center on designing, analyzing, and deploying ML systems rather than conducting independent research. Pure research roles are more likely to face scrutiny or denial at the port of entry.
How does TN visa sponsorship compare to H-1B for this role?
TN has no annual lottery, no cap for Canadians, and no multi-month USCIS adjudication wait. H-1B requires registration in March, lottery selection, and a lengthy petition process before you can start. For a qualified Canadian ML Manager, TN sponsorship can result in approval the same day you present at the border, making it dramatically faster to execute.
What documents does my employer need to prepare for my TN application?
Your employer must provide a detailed support letter on company letterhead stating your job title, USMCA classification, a description of qualifying duties, your salary, and the length of employment. Canadian applicants present this letter directly to CBP. Mexican nationals submit it as part of their DS-160 consular package. The letter is the centerpiece of your application and must be role-specific.
Where can I find Machine Learning Manager jobs that already offer TN visa sponsorship?
Migrate Mate lets you search specifically for Machine Learning Manager positions where employers have confirmed TN visa sponsorship. This avoids the common problem of applying to roles where the hiring team is unfamiliar with USMCA classifications and stalls or withdraws offers once the visa process starts.
Can I switch employers or get promoted while on TN status as an ML Manager?
Changing employers requires a new TN application tied to the new company. Canadians can handle this at a port of entry, but any gap in employment or a role change that shifts your duties outside the Computer Systems Analyst classification creates exposure. A promotion within the same employer that significantly changes your responsibilities should be reviewed to confirm it still supports your TN category.