Job Description Summary

As a GE Vernova accelerator, GE Vernova Advanced Research is driving strategy and leading research & development efforts to execute on the business’s mission to help power the energy transition. We forge the collaborations and help invent the technologies required to electrify and decarbonize for a zero-carbon future.

Representing virtually every major scientific and engineering discipline, our researchers are collaborating with GE Vernova’s businesses, the U.S. government, and more than 420 entities at the forefront of technology to execute on 150+ energy focused projects. Collectively, these research programs and initiatives aim to solve near term technical challenges, deliver next generation product advances, and drive long term breakthrough innovation to enable more affordable, reliable, sustainable, and secure energy.

Come and join our powerful, unified force with the energy to change the world. Our mission is BIG.

Our TRANSFORMATION is key – bringing the right businesses together to LEAD the ENERGY TRANSITION. Our TEAM is ready.

Addressing the climate crisis is an urgent global priority and we take our responsibility seriously. Building on over 130 years of experience tackling the world’s challenges, GE Vernova is uniquely positioned to help lead the energy transition by continuing to electrify the world while simultaneously working to decarbonize it. GE Vernova helps customers power economies and deliver electricity that is vital to health, safety, security, and improved quality of life.

Job Description

Foundation models for time-series data are general-purpose models pretrained on large-scale, diverse time-series datasets collected from various applications and domains. These models are capable of performing a wide range of time-series tasks, such as forecasting, classification, and anomaly detection. Similar to large language models (LLMs), time-series foundation models (TSFMs) are task- and application-agnostic, meaning that they can be trained and deployed at scale across different use cases.

We are looking for a graduate student with strong background on AI/ML and knowledge and experience working with time-series data, to research, develop, and test TSFMs for energy systems, such as gas turbines, wind turbines and power grid. This includes research on transformer-based architectures, model training and validation, and hyperparameter optimization over multiple GPUs.

Qualifications:

• Pursuing a PhD or a master's degree in AI, Computer Science, Estimation and Control Theory or related fields. 

• Legal authorization to work in the U.S. is required.

• 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.

• Must be willing to work out of an office located in Niskayuna, NY.

• Minimum GPA of 4.0/5.0 scale or 3.0/4.0 scale.

Desired Skills:

• Scientific curiosity and willingness to explore, learn, and innovate.

• Strong background on AI/ML, deep learning and mathematical optimization.

• Strong working knowledge in Python and machine learning frameworks (e.g. PyTorch, Tensor Flow).

• Familiarity with large-scale data storage and processing pipelines such as AWS.

• Familiarity with foundation models, LLM architectures, hyper-parameter optimization and fine-tuning techniques.

• Experience working with time-series data (for forecasting, anomaly detection, etc.).

• Experience with GPU training and parallelization.

The weekly base pay range for this position is $1,000-$2,000 weekly. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position will be posted until at least 9/23/2025.

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 di