Performance Modeling Intern - Seaglider Tech

REGENT; North Kingstown (RI); On-site; USD 32,000 - 42,000; Full time

Benefits offered by this job

Housing Stipend

Daily catered lunches

Learning & development

Job summary

REGENT is seeking a Performance Intern in Hardware Engineering to help build the modeling backbone for Seaglider performance. You will work deep in code, data, and models, connecting on-water test data to predictive tools, with ownership over the models and pipelines the team relies on.

This internship offers exposure to air-water vehicle dynamics, collaboration with engineers and operators, housing stipend, daily catered lunches, and opportunities to contribute to production-grade workflows.

Qualifications

• Solid grounding in aircraft performance modeling and aerodynamics.
• Proficient in Python or MATLAB with project evidence.
• Familiarity with optimization methods across tools.
• Experience with flight/test data analysis.
• Exposure to Git and CI/CD workflows.
• Clear communication and teamwork.

Responsibilities

• Update Vehicle Performance Models using real test data to improve accuracy for operations and development.
• Strengthen the performance toolset by improving workflows and pipelines.
• Push toward standardized, repeatable deliverables for performance data.
• Present progress and findings to the performance team in clear narratives.
• Document models, tools, and decisions for smooth handoffs after the internship.

Skills

Aerodynamics

Python/MATLAB

Optimization

Flight data

Collaboration

Git/CI

Tools

Git

CI/CD

Job description

REGENT is seeking a Performance Intern in Hardware Engineering to help build the modeling backbone for Seaglider performance. You will work deep in code, data, and models, connecting on-water test data to predictive tools, with ownership over the models and pipelines the team relies on.

This internship offers exposure to air-water vehicle dynamics, collaboration with engineers and operators, housing stipend, daily catered lunches, and opportunities to contribute to production-grade workflows.