TL;DR

Graduate Student Intern - Software Engineering (AI/ML): Exploring and applying AI/ML techniques to graph- or mesh-structured engineering data and developing AI-driven approaches for simulation. With an accent on Graph Neural Networks and physics-based applications. Focus on prototyping, testing, and evaluating AI models in simulation workflows and improving model accuracy and performance.

Location: Onsite in Austin, United States

Company

%hirify_global% hires and develops leaders and innovators who want to make an impact on the world of technology.

What you will do

Explore and apply AI/ML techniques, including Graph Neural Networks (GNNs), to graph- or mesh-structured engineering data.
Assist in developing AI-driven approaches for engineering and physics-based applications, such as thermal and structural simulation.
Work with researchers and engineers to prototype, test, and evaluate AI models in simulation workflows.
Analyze experimental results and help improve model accuracy and performance.
Contribute to technical discussions, documentation, and research or prototype code.

Requirements

Currently pursuing a Master’s degree or PhD in Computer Science, Engineering, or a related field.
Strong foundation in data structures and algorithms.
Programming experience in C/C++ and Python.
Familiarity with basic software development practices (debugging, version control).
Strong collaboration skills, curiosity, and motivation to learn.

Nice to have

Familiarity with mesh-based data structures or graph representations.
Coursework or project experience related to AI/ML.
Experience using GNNs for mesh- or graph-based engineering and simulation problems.
Exposure to EDA, CAD/CAE, or other simulation-based domains.
Interest in performance optimization, parallel computing, or GPU acceleration.
Experience with ML frameworks (e.g., PyTorch, TensorFlow).

Culture & Benefits

Work on impactful projects that matter, helping to solve what others can't.