J-1 Visa Software Systems Engineer Jobs
Software Systems Engineer roles in the United States are accessible to exchange visitors through the J-1 visa Trainee or Research Scholar program category, depending on your career stage. Securing sponsorship requires a designated State Department sponsor organization to issue your DS-2019, separate from your host employer.
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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 Software Systems Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new J-1 Visa Software Systems Engineer Jobs.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as a Software Systems Engineer
Verify your SOC code before applying
Software Systems Engineer maps to SOC 17-1199 or 15-1252 depending on the role. Confirm the exact code with your prospective host employer early, because your J-1 training plan must align with it for DOL compliance.
Build a training plan before outreach
J-1 Trainee sponsorship requires a detailed training plan showing structured skill development, not just job duties. Draft this document before approaching host employers so you can demonstrate program readiness from the first conversation.
Target hosts with established sponsor relationships
Use Migrate Mate to identify U.S. employers already hosting J-1 exchange visitors in engineering or technical roles, so your search focuses on organizations familiar with DS-2019 requirements and host-employer responsibilities.
Distinguish Research Scholar from Trainee categories
If your role involves original research at a university or research institute, Research Scholar sponsorship applies. If you're applying to a private-sector engineering team, Trainee is the correct category. Misidentifying your category delays DS-2019 issuance.
Confirm the home residency requirement upfront
Some Software Systems Engineer J-1 placements trigger the two-year home residency requirement based on funding source or skills list designation. Verify this before accepting an offer, since it affects your ability to pursue H-1B visa or green card pathways afterward.
Request the signed DS-7002 before your interview
USCIS and your designated sponsor both require the DS-7002 training plan to be signed by the host employer before your consular interview. Confirm the host has completed and countersigned it to avoid last-minute delays at the embassy.
Software Systems Engineer J-1 Visa: Frequently Asked Questions
Which J-1 program category fits a Software Systems Engineer role?
The Trainee category applies if you have a degree and at least one year of experience outside the U.S., or five years of work experience without a degree. The Research Scholar category applies if your role is primarily research-focused at a university or research institute. Private-sector engineering positions almost always fall under Trainee, not Research Scholar.
Who actually sponsors my J-1 visa, the employer or a separate organization?
Your host employer is not your visa sponsor. A U.S. Department of State-designated sponsor organization, such as Cultural Vistas, AIPT, or IIE, issues the DS-2019 form and administers your program. The host employer signs the training plan and provides the placement, but the designated sponsor holds legal responsibility for your exchange visitor status throughout the program.
How do I find U.S. employers open to hosting J-1 Software Systems Engineers?
Most employers don't advertise J-1 host positions explicitly, which makes targeted searching essential. Migrate Mate surfaces U.S. companies and roles aligned with J-1 sponsorship pathways for engineering professionals, so you can identify receptive hosts before investing time in outreach. Filtering by role type and industry narrows results to employers already familiar with exchange visitor compliance obligations.
Does the two-year home residency requirement apply to software engineering J-1 placements?
Not automatically. The two-year home residency requirement applies if your J-1 program is funded by your home government or the U.S. government, or if your home country's skills list includes your occupation. Software systems engineering may appear on certain countries' skills lists. Confirm your status directly with your designated sponsor before accepting an offer, since a waiver process can take six to twelve months if required.
What does the DS-7002 training plan need to cover for a systems engineering role?
The DS-7002 must document specific technical skills you'll develop, the phases of your training, the supervision structure, and measurable performance benchmarks. For a Software Systems Engineer, this typically means detailing methodology training, architecture exposure, code review participation, and any cross-functional project involvement. Generic job descriptions don't satisfy the requirement. Both you and the host employer must sign it before your designated sponsor issues the DS-2019.