GE Vernova – AGI – AI Post-Training and Model Alignment Intern - Summer 2027

Location: Bellevue

Job Description Summary

At GE Vernova's Applied Grid Innovation (AGI) team, we are exploring the next generation of AI technologies that will transform how electric utilities operate and manage the power grid. As a Power System Intern focused on foundational models, you will contribute to research and prototyping efforts that combine power system expertise with advanced AI capabilities to create intelligent operational solutions for the grid of the future.

Are you passionate about innovation? Are you excited at the opportunity to electrify and decarbonize the world?

We operate with a founder’s mindset. We deliver innovation with passion, speed, and courage. We continuously challenge our thinking and are empowered to dream big and take smart risks.

What impact you’ll make

As a student of the Applied Grid Innovation team you will be an active contributor to the development of next-generation AI systems that help utilities make more informed decisions and accelerate the transition toward an AI-native grid.

What you’ll do (Job Responsibilities)

• Research post-training techniques for foundation models.
• Explore fine-tuning, alignment, reinforcement learning, and feedback-driven learning approaches.
• Develop experiments to improve model performance on utility-specific tasks.
• Evaluate model behavior, accuracy, and domain adaptation.
• Support creation of datasets and training pipelines.
• Analyze tradeoffs between performance, cost, and operational value.
• Collaborate with AI researchers and software engineers.
• Present experimental findings and recommendations.

What you’ll bring (Basic Qualifications)

• Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Data Science, AI/ML, or related discipline.
• Experience with Python and machine learning frameworks.
• Understanding of supervised learning and deep learning fundamentals.
• Experience conducting research or model development projects.
• Strong analytical and problem-solving skills.
• What will make you stand out (Desired Qualifications)
• Experience with LLM fine-tuning and model alignment.
• Knowledge of reinforcement learning and preference optimization techniques.
• Experience with PyTorch, Hugging Face, or similar frameworks.
• Familiarity with generative AI technologies.
• Interest in energy systems and critical infrastructure applications.