Engineering Intern: FEA & AI-Driven Workflows (Houston)

HMH; Houston (TX); On-site; USD 25,000 - 33,000; Full time

Job summary

HMH is seeking an Engineering Intern to support the Engineering Technical Services team by contributing to finite element analysis (FEA) using Ansys, data analysis to drive process improvement, and exploring AI-enabled tools to enhance engineering workflows.

The Intern will learn FEA principles, apply AI-enabled tools with human review, and work with engineers on tasks such as model setup, meshing, boundary conditions, and data-driven optimization.

Qualifications

• Currently pursuing a Bachelor's or Graduate degree in Mechanical Engineering, Computational Engineering, or related field.
• GPA 3.0+ preferred
• Strong analytical and communication skills
• Experience with Ansys or other FEA software is preferred

Responsibilities

• Support FEA activities using Ansys, including model setup, meshing, and boundary conditions.
• Assist with material property assignments, solver execution, and evaluation of analysis results under supervision.
• Analyze engineering and operational data to identify trends and opportunities for process improvement.
• Evaluate and apply AI-enabled tools to automate repetitive tasks under human review.
• Other duties as assigned.

Skills

Analytical skills

Communication

Team collaboration

Independent work

Problem solving

Attention to detail

Ansys familiarity

Python

Education

Bachelor's or Graduate degree in Mechanical Engineering or Computational Engineering

Tools

Ansys

Python

MATLAB

Power BI

Excel

Job description

HMH is seeking an Engineering Intern to support the Engineering Technical Services team by contributing to finite element analysis (FEA) using Ansys, data analysis to drive process improvement, and exploring AI-enabled tools to enhance engineering workflows.

The Intern will learn FEA principles, apply AI-enabled tools with human review, and work with engineers on tasks such as model setup, meshing, boundary conditions, and data-driven optimization.