AI Benchmarking Intern - Foundation Models for Power Grids

GE Vernova; Bellevue (WA); Sur place; USD 22 000 - 31 000; Plein temps

Avantages offerts par ce poste

Relocation Assistance

Housing Allowance

Employee Assistance Program

GE Vernova Retirement Savings Plan

Résumé du poste

GE Vernova's Applied Grid Innovation team in Bellevue, WA is seeking a Power System Intern focused on foundational models to advance AI methods for grid operations. You will develop benchmarks, datasets, and evaluation frameworks to ensure reliable, explainable AI for critical utility applications.

The role emphasizes Python, data analysis, and ML techniques, with collaboration across power systems and AI. Internship dates: May 2027–August 2027, relocation/housing support provided.

Qualifications

• Currently pursuing a Bachelor's, Master's, or PhD in Electrical Engineering, Computer Engineering, Power Systems or related discipline.
• Experience with Python programming.
• Familiarity with machine learning evaluation concepts.
• Experience analyzing data and generating insights.
• Strong quantitative and analytical abilities.

Responsabilités

• Develop benchmarks for evaluating AI and foundation model performance.
• Design testing methodologies and evaluation frameworks.
• Create datasets and scenarios for model validation.
• Measure model quality, reliability, accuracy, and operational usefulness.
• Analyze benchmark results and identify improvement opportunities.
• Evaluate competing AI solutions across multiple dimensions.
• Support continuous improvement of AGI AI capabilities.
• Communicate findings through reports and presentations.

Connaissances

Python programming

ML evaluation

Data analysis

Quantitative analysis

Formation

Bachelor's/Master's/PhD in Electrical Engineering, Computer Engineering, Power Systems

Description du poste

GE Vernova's Applied Grid Innovation team in Bellevue, WA is seeking a Power System Intern focused on foundational models to advance AI methods for grid operations. You will develop benchmarks, datasets, and evaluation frameworks to ensure reliable, explainable AI for critical utility applications.

The role emphasizes Python, data analysis, and ML techniques, with collaboration across power systems and AI. Internship dates: May 2027–August 2027, relocation/housing support provided.