J-1 Visa Systems Engineer Jobs
Systems Engineer roles in the United States are available to international professionals through the J-1 visa under the Trainee or Research Scholar program category, depending on your career stage. Qualifying positions require a designated sponsor organization to issue your DS-2019 and provide sponsorship. No lottery or annual cap applies.
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Get Access To All JobsThe Energy and Photon Science Directorate advances basic science that underpins discoveries and breakthroughs for energy systems. The appointment will be for a one-year with an opportunity for a one-year renewal to perform research in the area of electric power grids based on funding and individual performance.
The successful candidate will contribute to the development of next-generation AI foundation models and AI-enabled workflows for electric applications. In particular, the position focuses on advancing GridFM, a grid foundation model for power systems.
The role offers unique opportunities to contribute to cutting-edge research while helping translate AI innovations into real-world utility applications that support grid modernization, resilience, and large-scale electrification.
Essential Duties and Responsibilities:
- Extend current GridFM capabilities for distribution networks
- Develop scalable graph-based machine learning or related models
- Expand training data generation capabilities
- Create benchmarks and test developed models
Required Knowledge, Skills, and Abilities:
- Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field.
- Strong background in machine learning and deep learning.
- Experience with PyTorch, JAX, TensorFlow, or similar frameworks.
- Some experience developing Graph Neural Networks (GNNs), Graph Transformers, or foundation-model architectures.
- Familiarity with model training, fine-tuning, evaluation, and deployment.
- Understanding of uncertainty quantification, model robustness, and physics-informed AI.
- Experience with GPU computing and large-scale model training.
- Demonstrated ability to conduct independent research.
Preferred Knowledge, Skills, and Abilities:
- Familiarity with distributed computing, HPC environments, and cloud platforms.
- Experience building production-quality software and ML pipelines.
- Familiarity with Git, CI/CD, containerization (Docker), and reproducible workflows.
- Experience developing APIs and workflow orchestration systems.
- Experience optimizing AI workloads for performance and scalability.
- Basic knowledge of electric power systems, transmission/distribution networks, power flow, optimal power flow, contingency analysis, or grid planning.
- Familiarity with tools such as PowerModels, MATPOWER, PSS/E, GridLAB-D, OpenDSS, or similar.
- Experience with mathematical optimization, mixed-integer programming, stochastic optimization, or decision analytics.
- Familiarity with Gurobi, CPLEX, Pyomo, JuMP, or related tools.
- Experience with LLM-based workflows, tool-calling agents, MCP architectures, retrieval systems, or AI copilots.
- Familiarity with multi-agent systems and decision-support applications.
Other Information:
Candidates must have completed all degree requirements by the commencement of employment. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events.
Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $70,200 - $85,000/ year. You will be placed at the level and salary commensurate with your experience. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.
Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more information at BNL | Benefits Program
Brookhaven National Laboratory requires all non-badged personnel including visitors to produce a REAL-ID or REAL-ID compliant documentation to access Brookhaven National Laboratory. This is due to nationwide identification requirements for federal site access as required by the federal REAL ID Act. Those not in possession of a REAL ID-compliant document will not be permitted to access the site which includes access to the Laboratory for interviews.
As a U.S. Department of Energy laboratory, Brookhaven National Laboratory requires employees to obtain and maintain a DOE Uncleared Personal Identity Verification (UPIV) credential in accordance with Homeland Security Presidential Directive 12 (HSPD-12) requirements. The credentialing process is completed as part of onboarding and enables access to DOE facilities and information systems. As a condition of employment, the selected candidate must be able to obtain and maintain a UPIV credential. These requirements are established under DOE Order 206.2 Chg. 2, Identity, Credential, and Access Management (ICAM), and DOE Order 473.1A- Physical Protection Program.
About us
Brookhaven National Laboratory delivers discovery science and transformative technology to power and secure the nation’s future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy’s (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country.
Equal Opportunity/Affirmative Action Employer
Guided by our core values of integrity, responsibility, innovation, respect, and teamwork, Brookhaven Science Associates is an Equal Employment Opportunity Employer-Vets/Disabled. We are committed to fostering a respectful and collaborative environment that fuels scientific discovery. We consider all qualified applicants without regard to any characteristic protected by law. All qualified individuals are encouraged to apply. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. VEVRAA Federal Contractor
BSA employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. The full text of the Order may be found at: https://www.directives.doe.gov/directives-documents/400-series/0486.1-BOrder-a/@@images/file
The Energy and Photon Science Directorate advances basic science that underpins discoveries and breakthroughs for energy systems. The appointment will be for a one-year with an opportunity for a one-year renewal to perform research in the area of electric power grids based on funding and individual performance.
The successful candidate will contribute to the development of next-generation AI foundation models and AI-enabled workflows for electric applications. In particular, the position focuses on advancing GridFM, a grid foundation model for power systems.
The role offers unique opportunities to contribute to cutting-edge research while helping translate AI innovations into real-world utility applications that support grid modernization, resilience, and large-scale electrification.
Essential Duties and Responsibilities:
- Extend current GridFM capabilities for distribution networks
- Develop scalable graph-based machine learning or related models
- Expand training data generation capabilities
- Create benchmarks and test developed models
Required Knowledge, Skills, and Abilities:
- Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field.
- Strong background in machine learning and deep learning.
- Experience with PyTorch, JAX, TensorFlow, or similar frameworks.
- Some experience developing Graph Neural Networks (GNNs), Graph Transformers, or foundation-model architectures.
- Familiarity with model training, fine-tuning, evaluation, and deployment.
- Understanding of uncertainty quantification, model robustness, and physics-informed AI.
- Experience with GPU computing and large-scale model training.
- Demonstrated ability to conduct independent research.
Preferred Knowledge, Skills, and Abilities:
- Familiarity with distributed computing, HPC environments, and cloud platforms.
- Experience building production-quality software and ML pipelines.
- Familiarity with Git, CI/CD, containerization (Docker), and reproducible workflows.
- Experience developing APIs and workflow orchestration systems.
- Experience optimizing AI workloads for performance and scalability.
- Basic knowledge of electric power systems, transmission/distribution networks, power flow, optimal power flow, contingency analysis, or grid planning.
- Familiarity with tools such as PowerModels, MATPOWER, PSS/E, GridLAB-D, OpenDSS, or similar.
- Experience with mathematical optimization, mixed-integer programming, stochastic optimization, or decision analytics.
- Familiarity with Gurobi, CPLEX, Pyomo, JuMP, or related tools.
- Experience with LLM-based workflows, tool-calling agents, MCP architectures, retrieval systems, or AI copilots.
- Familiarity with multi-agent systems and decision-support applications.
Other Information:
Candidates must have completed all degree requirements by the commencement of employment. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events.
Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $70,200 - $85,000/ year. You will be placed at the level and salary commensurate with your experience. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.
Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more information at BNL | Benefits Program
Brookhaven National Laboratory requires all non-badged personnel including visitors to produce a REAL-ID or REAL-ID compliant documentation to access Brookhaven National Laboratory. This is due to nationwide identification requirements for federal site access as required by the federal REAL ID Act. Those not in possession of a REAL ID-compliant document will not be permitted to access the site which includes access to the Laboratory for interviews.
As a U.S. Department of Energy laboratory, Brookhaven National Laboratory requires employees to obtain and maintain a DOE Uncleared Personal Identity Verification (UPIV) credential in accordance with Homeland Security Presidential Directive 12 (HSPD-12) requirements. The credentialing process is completed as part of onboarding and enables access to DOE facilities and information systems. As a condition of employment, the selected candidate must be able to obtain and maintain a UPIV credential. These requirements are established under DOE Order 206.2 Chg. 2, Identity, Credential, and Access Management (ICAM), and DOE Order 473.1A- Physical Protection Program.
About us
Brookhaven National Laboratory delivers discovery science and transformative technology to power and secure the nation’s future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy’s (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country.
Equal Opportunity/Affirmative Action Employer
Guided by our core values of integrity, responsibility, innovation, respect, and teamwork, Brookhaven Science Associates is an Equal Employment Opportunity Employer-Vets/Disabled. We are committed to fostering a respectful and collaborative environment that fuels scientific discovery. We consider all qualified applicants without regard to any characteristic protected by law. All qualified individuals are encouraged to apply. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. VEVRAA Federal Contractor
BSA employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. The full text of the Order may be found at: https://www.directives.doe.gov/directives-documents/400-series/0486.1-BOrder-a/@@images/file
See all 37+ J-1 Visa Systems Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new J-1 Visa Systems Engineer Jobs.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as a Systems Engineer
Align your degree with SOC codes
Systems Engineer roles map to SOC 17-2199 in O*NET. Confirm your degree field matches the technical discipline of the posted role before applying, since designated sponsors verify this alignment when approving your DS-2019.
Identify your correct J-1 category early
If you're currently enrolled in a degree program, you qualify under the Intern category. If you've graduated within the past year, Trainee applies. Applying under the wrong category causes DS-2019 rejections that delay your start date by weeks.
Draft a training plan before outreach
Host employers must submit a structured training plan to the designated sponsor. Arrive at interviews with a draft outlining your learning objectives, technical milestones, and supervision structure, since many engineering hiring managers don't know what sponsors require.
Search Migrate Mate for J-1-aligned openings
Filter systems engineering roles on Migrate Mate by J-1 visa compatibility to surface host employers already familiar with the designated sponsor workflow, saving you the step of educating a recruiter from scratch.
Check the 2-year home residency requirement upfront
Government-funded J-1 exchange visitors and those from countries on the State Department skills list face a two-year home residency requirement before changing to H-1B visa or green card status. Confirm your situation with your sponsor before signing an offer.
Verify host employer acceptance before sponsor enrollment
Designated sponsors such as Cultural Vistas or AIPT require written confirmation of your host employer placement before they issue a DS-2019. Secure a signed offer letter or formal placement agreement first, or your sponsor application stalls at intake.
Systems Engineer J-1 Visa: Frequently Asked Questions
Which J-1 program category fits a Systems Engineer role?
It depends on your career stage. Current students completing a degree in engineering or a related technical field typically fall under the Intern category. Professionals who have graduated and are pursuing supervised on-the-job training qualify under the Trainee category. Researchers working in advanced systems or defense engineering at universities or national labs may qualify under Research Scholar or Specialist, depending on the host institution.
Who actually sponsors a J-1 visa for a Systems Engineer, the employer or a third party?
The visa sponsor is a U.S. Department of State-designated organization, not the hiring employer. Organizations such as Cultural Vistas, AIPT, or IIE issue your DS-2019, approve your training plan, and monitor compliance throughout your exchange. Your employer is the host organization. The two roles are legally separate, and confusing them often causes delays when candidates approach employers expecting direct visa sponsorship.
Can I use Migrate Mate to find Systems Engineer roles that accept J-1 exchange visitors?
Yes. Migrate Mate lets you filter Systems Engineer openings by J-1 visa compatibility, which surfaces host employers already working within the designated sponsor framework. That matters because systems engineering roles at companies unfamiliar with the DS-2019 process often stall during onboarding, and targeting experienced host employers reduces that risk significantly.
Does the two-year home residency requirement apply to Systems Engineers on a J-1 visa?
It applies in specific circumstances, not universally. If your J-1 program was funded by your home country's government, the U.S. government, or if your occupation appears on your country's State Department skills list, you're subject to the two-year requirement before switching to H-1B or pursuing a green card. Many private-sector systems engineering Trainee placements are not government-funded, so the requirement may not apply, but you must confirm this with your designated sponsor before accepting an offer.
What documentation does a host employer need to complete before my J-1 can be issued?
The host employer must sign a formal training plan, typically Form DS-7002 for Intern and Trainee categories, outlining your technical learning objectives, supervision structure, and evaluation schedule. The designated sponsor reviews and approves this plan before issuing your DS-2019. Systems engineering roles often require the host to document hands-on experience with specific platforms or infrastructure, so the more detailed your plan, the faster sponsor approval moves.