J-1 Visa Machine Learning Scientist Jobs
Machine Learning Scientist roles in the United States are accessible to international researchers and professionals through J-1 visa sponsorship, most commonly under the Research Scholar or Trainee program category. Designated sponsors issue the DS-2019, while your host institution or company provides the research environment and training plan.
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Postdoctoral Fellow in Water Systems (ml)
Hiring Department:
Bureau of Economic Geology
Position Open To:
All Applicants
Weekly Scheduled Hours:
40
FLSA Status:
Exempt
Earliest Start Date:
Immediately
Position Duration:
Expected to Continue Until Aug 03, 2026
Location:
PICKLE RESEARCH CAMPUS
Job Details:
General Notes
A researcher with a strong background in hydrology, numerical/analytical modeling, programming, and data management/analytics is needed to support existing and forthcoming projects in the BEG hydro group.
Purpose
We are seeking highly motivated candidates for postdoctoral fellow positions within the Bureau’s hydrology research group. These fellows will be key members of an expanding research program focused on assessing Texas water resources and systems in service to our mission as the state geological survey. The current research program objectives are: (a) synthesize a full suite of Texas water resource and system data into a common spatiotemporal framework, (b) develop a web-based product to deliver accessible and actionable water resource and system information to stakeholders, (c) assess the historical impact of drought and flood on water resources and systems, and (d) evaluate drought and flood risk and resilience. This research program is anticipated to yield significant insights for Texas water resource management and planning processes as well as to provide a strong foundation for further research projects. Each position term is subject to performance as well as research program needs and funding. Multiple postdoctoral fellow positions are initially available, and candidates are strongly encouraged to review Preferred Qualifications to determine which position is best aligned with their skills and experience.
Responsibilities
-
Perform research in the hydrology field, including analysis and interpretation of large datasets using various analytical, statistical, and numerical techniques.
-
Contribute to the publication of scientific papers and presentation of findings to scholarly meetings and stakeholders.
-
Collaborate and coordinate with research program team members and participate in program development through proposals and other fundraising.
-
In addition to other duties as assigned, provide support and service as needed to supervisor, the Bureau, and the Jackson School.
Required Qualifications
Ph.D. acquired within the last three years in Earth Science (e.g. Hydrology, Hydrogeology, Geology, Geography), Civil Engineering, or closely related field. Demonstrated experience and aptitude in a hydrology context with: (a) data analytics, wrangling, management, and synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development. Demonstrated ability to meet deadlines and effectively disseminate research project results to professional peers. Excellent written and oral communication skills. Professional demeanor and strong interpersonal skills.
Degree must have been obtained within 3 years from date of hire.
Preferred Qualifications
Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as convolutional neural networks (CNNs), generative AI methods such as diffusion models, and interpretability techniques commonly applied in hydrology including SHAP or LIME for explaining outputs of forecasting models, (d) experience in using high performance computing systems with multiple nodes and GPUs and (e) drought metrics. Familiarity with Texas water resources and management practices. Experience working within an integrated team of scientists, engineers, and economists in a dynamic environment.
Salary Range
$65,000+ depending on qualifications.
Working Conditions
-
May work in all weather conditions
-
May work in extreme temperatures
-
May work around standard office conditions
-
Repetitive use of a keyboard at a workstation
-
Occasional weekend, overtime, and evening work to meet deadlines
-
Fieldwork as necessary
Required Materials
-
Resume/CV
-
3 work references with their contact information
-
Letter of interest
Employment Eligibility:
Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
- E-Verify Poster (English and Spanish) [PDF]
- Right to Work Poster (English) [PDF]
- Right to Work Poster (Spanish) [PDF]
Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.
Job Posting Title:
Postdoctoral Fellow in Water Systems (ml)
Hiring Department:
Bureau of Economic Geology
Position Open To:
All Applicants
Weekly Scheduled Hours:
40
FLSA Status:
Exempt
Earliest Start Date:
Immediately
Position Duration:
Expected to Continue Until Aug 03, 2026
Location:
PICKLE RESEARCH CAMPUS
Job Details:
General Notes
A researcher with a strong background in hydrology, numerical/analytical modeling, programming, and data management/analytics is needed to support existing and forthcoming projects in the BEG hydro group.
Purpose
We are seeking highly motivated candidates for postdoctoral fellow positions within the Bureau’s hydrology research group. These fellows will be key members of an expanding research program focused on assessing Texas water resources and systems in service to our mission as the state geological survey. The current research program objectives are: (a) synthesize a full suite of Texas water resource and system data into a common spatiotemporal framework, (b) develop a web-based product to deliver accessible and actionable water resource and system information to stakeholders, (c) assess the historical impact of drought and flood on water resources and systems, and (d) evaluate drought and flood risk and resilience. This research program is anticipated to yield significant insights for Texas water resource management and planning processes as well as to provide a strong foundation for further research projects. Each position term is subject to performance as well as research program needs and funding. Multiple postdoctoral fellow positions are initially available, and candidates are strongly encouraged to review Preferred Qualifications to determine which position is best aligned with their skills and experience.
Responsibilities
-
Perform research in the hydrology field, including analysis and interpretation of large datasets using various analytical, statistical, and numerical techniques.
-
Contribute to the publication of scientific papers and presentation of findings to scholarly meetings and stakeholders.
-
Collaborate and coordinate with research program team members and participate in program development through proposals and other fundraising.
-
In addition to other duties as assigned, provide support and service as needed to supervisor, the Bureau, and the Jackson School.
Required Qualifications
Ph.D. acquired within the last three years in Earth Science (e.g. Hydrology, Hydrogeology, Geology, Geography), Civil Engineering, or closely related field. Demonstrated experience and aptitude in a hydrology context with: (a) data analytics, wrangling, management, and synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development. Demonstrated ability to meet deadlines and effectively disseminate research project results to professional peers. Excellent written and oral communication skills. Professional demeanor and strong interpersonal skills.
Degree must have been obtained within 3 years from date of hire.
Preferred Qualifications
Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as convolutional neural networks (CNNs), generative AI methods such as diffusion models, and interpretability techniques commonly applied in hydrology including SHAP or LIME for explaining outputs of forecasting models, (d) experience in using high performance computing systems with multiple nodes and GPUs and (e) drought metrics. Familiarity with Texas water resources and management practices. Experience working within an integrated team of scientists, engineers, and economists in a dynamic environment.
Salary Range
$65,000+ depending on qualifications.
Working Conditions
-
May work in all weather conditions
-
May work in extreme temperatures
-
May work around standard office conditions
-
Repetitive use of a keyboard at a workstation
-
Occasional weekend, overtime, and evening work to meet deadlines
-
Fieldwork as necessary
Required Materials
-
Resume/CV
-
3 work references with their contact information
-
Letter of interest
Employment Eligibility:
Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
- E-Verify Poster (English and Spanish) [PDF]
- Right to Work Poster (English) [PDF]
- Right to Work Poster (Spanish) [PDF]
Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.
See all J-1 Visa Machine Learning Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new J-1 Visa Machine Learning Scientist Jobs.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as a Machine Learning Scientist
Align your CV to specialty occupation standards
Research Scholar and Trainee DS-2019 applications require documented evidence of your academic credentials and research focus. Structure your CV around peer-reviewed publications, model architectures, and dataset contributions rather than general software skills.
Distinguish Research Scholar from Trainee eligibility
Research Scholar status fits postdoctoral researchers and faculty-level scientists at accredited institutions. Trainee status suits early-career professionals outside academia. Applying under the wrong category triggers DS-2019 refusal, so confirm your employment history matches the program definition before your host submits paperwork.
Flag the two-year home residency requirement early
Machine Learning Scientists funded by a government or international organization, or from a country on the Exchange Visitor Skills List, may face the two-year home residency requirement under INA 212(e). Confirm your funding source and nationality status before accepting an offer, since this requirement blocks H-1B visa and green card transitions until fulfilled or waived.
Target host organizations with active DS-2019 pipelines
Use Migrate Mate to identify U.S. employers and research institutions already hosting J-1 visa exchange visitors in machine learning and AI roles. A host with an established relationship with a designated sponsor moves your DS-2019 process faster than one filing for the first time.
Require a signed Training Plan before your interview
Consular officers and designated sponsors both review the J-1 Training Plan, which must detail specific machine learning methodologies, tools, and learning objectives by phase. Vague plans citing only 'AI research' are routinely rejected. Your host employer writes the plan, but you should review it against your actual role before submission.
Negotiate program duration against your research timeline
Research Scholar J-1 status is granted for the duration of the exchange program, capped by the host's DS-2019 dates. If your machine learning project has a defined deliverable, negotiate a program end date that clears peer review or publication deadlines, since extensions require a new DS-2019 and designated sponsor approval.
Machine Learning Scientist J-1 Visa: Frequently Asked Questions
Which J-1 program category fits a Machine Learning Scientist role?
The category depends on your career stage and work setting. Postdoctoral researchers and faculty-level scientists conducting independent research at universities or research institutes typically qualify as Research Scholars. Professionals employed at private-sector AI labs or tech companies, usually within five years of their qualifying degree, qualify as Trainees. Students completing a degree-related practical assignment may qualify under the Intern category instead.
Who actually sponsors the J-1 visa for a Machine Learning Scientist?
The visa sponsor is a U.S. Department of State-designated exchange visitor program sponsor, not your employer. Organizations like IIE, CIEE, and Cultural Vistas issue the DS-2019 form and carry legal responsibility for program compliance. Your employer is the host organization, providing the lab environment and signing the Training Plan, but it does not hold sponsorship authority unless it is itself a designated sponsor.
How do I find U.S. employers open to hosting J-1 Machine Learning Scientists?
Most job boards don't filter by J-1 host eligibility, which makes identifying willing employers time-consuming. Migrate Mate lets you search specifically for U.S. roles and employers that align with J-1 sponsorship in technical fields, so you can focus outreach on organizations already familiar with the DS-2019 process rather than cold-educating hiring managers from scratch.
Does the two-year home residency requirement apply to machine learning roles?
It can, depending on your funding source and country of origin. If your exchange is funded by your home government, the U.S. government, or an international organization, or if your nationality appears on the Exchange Visitor Skills List under a relevant field like computing or engineering, INA 212(e) applies. This blocks you from changing to H-1B or adjusting status until the requirement is fulfilled or formally waived.
What should the J-1 Training Plan include for a Machine Learning Scientist?
The Training Plan must go beyond a general job description. It needs to specify the machine learning frameworks you'll work with, the research objectives broken into phases, measurable learning outcomes, and how each phase builds technical competency. Designated sponsors and consular officers reject plans that read as regular employment contracts rather than structured exchange programs. Your host drafts the plan, but reviewing it for specificity before submission protects your application.