GE Vernova AI Research Intern for Grid Modeling and Forecasting

Job Description Summary

Job Description

Join our AI research team to help create the intelligent electric grid of the future. As an AI Research Intern, you will focus on one of the most critical challenges in the energy transition: ensuring a stable, efficient, and resilient power grid. Your primary objective will be to develop and demonstrate advanced machine learning models for large-scale grid optimization and forecasting.

This project goes beyond traditional data-driven approaches. A key component of your work will be to integrate fundamental physics and domain knowledge—such as grid topology, power flow equations, and operational constraints—into your machine learning models. You will explore hybrid AI techniques to create practical, accurate, and robust solutions. Your work will have impact in improving grid operations, enabling higher penetration of renewable energy, and enhancing overall system reliability.

Project Outcomes:

* Comprehensive Validation & Report: A detailed technical report and a final presentation summarizing the model's architecture, methodology, and a rigorous evaluation of its performance against traditional and purely data-driven methods.
*  Validated Codebase for Grid Modeling: A well-documented, reusable codebase for the developed model and experiments, contributed to the team’s repository to support future grid-related research.
*  Potential Contribution to Intellectual Property: Novel techniques for integrating physics into grid-focused AI models that could form the basis of a patent application or a publication in a leading energy or AI conference/workshop.

Primary Skills Developed:

*  Grid Domain-Specific AI Application: Ability to translate complex challenges from grid operations/forecasting into well-defined AI problems and deliver effective, data-driven solutions.  
*  Applied Research & Development Lifecycle: Practical experience of the end-to-end research process in an industrial setting—from problem formulation and experimental design to prototyping, rigorous validation, and results analysis.
*  Technical Communication & Documentation: Advanced skills in documenting complex code, articulating novel modeling concepts in technical reports, and presenting research findings to a team of domain experts and business stakeholders.

Basic Qualifications:

• Currently pursuing a M.S./Ph.D. in Computer Science or related fields in MIT School of Engineering (EECS, MechE, etc.), Schwarzman College of Computing, or School of Science (Mathematics)
• Legal authorization to work in the U.S. is required.
• Must be willing to work out of an office located in Niskayuna, NY. 
• Minimum GPA 4.0 / 5.0 scale.
Because of the specific categories of data handled by GE Vernova Advanced Research and the structure of our work environment, we are unable to accommodate employment of persons while they are considered nationals of countries subject to comprehensive restrictions under the US Export Administration Regulations (EAR), 15 CFR Section 746 et seq. (currently North Korea, Syria, Iran and Cuba). Please note that citizens of these countries who have either “U.S. person” status under U.S. export control laws or subsequent citizenship or permanent residency from a non-restricted country can be considered.

Desired Qualifications:

• Demonstrated proficiency in programming languages, such as Python
• Solid understanding of AI and machine learning principles (including graph neural networks, transformer models)
• Experience with AI problems and applications with power systems, grid, or networks
• Hands-on experience with machine learning model development and model training on GPUs
• Ability to work collaboratively within cross-functional teams

Benefits Available to you:

Addressing the climate crisis is an urgent global priority, and at GE Vernova, we take our responsibility seriously. That is the singular mission of GE Vernova: to continue electrifying the world while simultaneously working to help decarbonize it. In order to meet this mission, we provide varied, competitive benefits to help support our workforce: Our Culture | GE Vernova (gecareers.com)

The pay for this position ranges from $1,000-2,000 weekly based on years of graduate field of study completed.

This position is also eligible for:

• Relocation Assistance: Co-op/Interns will be reimbursed for reasonable, proper, and documented expenditures incurred while initially reporting to work and returning to school/home upon completion of the assignment. Employees with a permanent address greater than 50 miles away from the work location are eligible.
• Housing Allowance: Co-op/Interns employees receive a weekly housing allowance to help off-set living expenses when the co-op/Intern’s permanent residence is at least 50 miles away from the work location.
• Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
• GE Retirement Savings Plan (RSP) after their accumulated service reaches 90 days, and they meet any other eligibility requirements as defined in the plans. (Eligibility occurs on the 1st of the month following the 90th day.)

General Electric Company, Ropcor, Inc., their successors, and in some cases their affiliates, each sponsor certain employee benefit plans or programs (i.e., is a Sponsor”). Each Sponsor reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a Sponsor’s welfare benefit plan or program. This document does not create a contract of employment with any individual.

Inclusion

At GE Vernova, we believe in the value of your unique identity, background and experiences. We are committed to fostering an inclusive culture, where everyone feels empowered to do their best work because they feel accepted, respected and that they belong.  Click here to learn more: https://jobs.gecareers.com/vernova/global/en/i-d-e

This position will remain open until at least November 1, 2025.

Additional Information