AI Foundations: Post-Training & Alignment Intern

Aimlroles; Bellevue (WA); On-site; USD 28,000 - 48,000; Part time

Benefits offered by this job

Relocation Assistance

Housing Allowance

Employee Assistance Program

Retirement Savings Plan

Job summary

GE Vernova’s Applied Grid Innovation team seeks a Power System Intern focused on foundational models in Bellevue, WA. You will contribute to research and prototyping that combine power systems with AI to create intelligent grid solutions for the future.

As a student, you will research post-training techniques, fine-tuning, and model evaluation, collaborating with AI researchers and engineers to present findings and recommendations for deployment in utility settings.

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.

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.

Skills

Python

ML frameworks

Supervised learning

Research experience

Analytical skills

Education

Bachelor’s/Master’s/PhD in CS/DS/AI/ML

Tools

PyTorch/Hugging Face

Job description

GE Vernova’s Applied Grid Innovation team seeks a Power System Intern focused on foundational models in Bellevue, WA. You will contribute to research and prototyping that combine power systems with AI to create intelligent grid solutions for the future.

As a student, you will research post-training techniques, fine-tuning, and model evaluation, collaborating with AI researchers and engineers to present findings and recommendations for deployment in utility settings.