ML Engineer Visa Sponsorship Jobs in Maryland
Maryland's ML engineer job market centers on the Baltimore-Washington corridor, with major employers including Leidos, Booz Allen Hamilton, Northrop Grumman, and Johns Hopkins Applied Physics Laboratory. Federal contracting and biomedical research drive consistent demand, and proximity to NSA and NIH creates specialized opportunities that regularly come with visa sponsorship.
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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
ML Engineer Job Roles in Maryland
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Search ML Engineer Jobs in MarylandML Engineer Jobs in Maryland: Frequently Asked Questions
Which companies sponsor visas for ML engineers in Maryland?
Federal contractors and defense firms are among the most active sponsors for ML engineers in Maryland. Booz Allen Hamilton, Leidos, Northrop Grumman, and SAIC regularly file H-1B visa petitions for machine learning roles. Johns Hopkins University and its Applied Physics Laboratory also sponsor ML talent, particularly for research-oriented positions. Technology consulting firms and healthcare analytics companies in the Baltimore and Bethesda areas contribute additional sponsorship activity.
Which visa types are most common for ML engineer roles in Maryland?
The H-1B is the most common visa category for ML engineers in Maryland, as machine learning roles typically qualify as specialty occupations requiring at least a bachelor's degree in computer science, data science, or a related field. OPT and STEM OPT extensions are widely used by graduates from University of Maryland and Johns Hopkins. Some research-focused positions at universities may also support J-1 visa or O-1 visa classifications depending on the candidate's profile.
How to find ml engineer visa sponsorship jobs in Maryland?
Migrate Mate filters ML engineer jobs in Maryland specifically by visa sponsorship willingness, saving you from applying to roles where sponsorship isn't available. Given Maryland's concentration of federal contractors and research institutions, it's worth filtering by employer type as well as location. Migrate Mate surfaces active sponsoring employers across the Baltimore-Washington corridor, including both private sector and government-adjacent organizations that hire ML engineers.
Which cities in Maryland have the most ML engineer sponsorship jobs?
Bethesda and Rockville in Montgomery County have the highest concentration of ML engineering sponsorship roles, driven by proximity to federal agencies, NIH-affiliated organizations, and technology contractors. Baltimore follows closely, anchored by Johns Hopkins, UMBC, and a growing health-tech sector. Columbia and Gaithersburg also see consistent ML hiring, particularly from defense and cybersecurity firms operating between Washington, D.C., and Baltimore.
Are there any Maryland-specific considerations for ML engineers seeking visa sponsorship?
Many high-demand ML roles in Maryland involve federal contracts or sensitive government work, which can require security clearances. Sponsorship for those positions is often restricted to candidates already authorized to work in the U.S., so it's worth confirming clearance requirements before applying. Maryland's university pipeline, particularly from University of Maryland College Park and UMBC, means employers in the region are generally familiar with OPT and STEM OPT timelines for new graduates.
What is the prevailing wage for sponsored ml engineer jobs in Maryland?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.