AI Engineer Intern: Vision, LLMs & Edge AI

Terracon; Austin (TX); On-site; USD 28,000 - 41,000; Full time

Job summary

Terracon is seeking a hands-on AI Engineering Intern to work on practical AI systems deployed in engineering and infrastructure environments. This is not a research-only position.

You will help develop AI tools that analyze pavement imagery, automate engineering workflows, build AI agents, retrieve knowledge from large document collections, and support next-generation digital products. Projects include computer vision, big language models (LLMs), RAG, GIS integration and edge AI deployment.

Qualifications

• Pursuing BS/MS in Computer Science, AI, ML, Data Science, Robotics or related field.
• Strong Python experience and practical project work.
• Experience with at least one ML framework (PyTorch, TensorFlow, Ultralytics YOLO, Detectron2 or HuggingFace).
• Experience using LLMs beyond prompting.

Responsibilities

• Build and improve AI agents using modern LLM frameworks.
• Develop RAG systems that search engineering documents and project archives.
• Train and evaluate computer vision models for pavement distress detection.
• Process and analyze drone, GoPro, LiDAR, and roadway imagery.
• Create image annotation, quality-control, and training pipelines.
• Experiment with edge AI deployment on NVIDIA Jetson hardware.
• Build internal applications using Python, Azure AI, Copilot Studio, and APIs.
• Integrate AI outputs with GIS, dashboards, and engineering workflows.
• Evaluate commercial AI tools and benchmark them against internal solutions.
• Prototype ideas quickly and present findings to engineers and leadership.

Skills

Python

LLM frameworks

Education

BS in Computer Science

MS in Artificial Intelligence

Tools

PyTorch

TensorFlow

Ultralytics YOLO

Detectron2

HuggingFace

Job description

Terracon is seeking a hands-on AI Engineering Intern to work on practical AI systems deployed in engineering and infrastructure environments. This is not a research-only position.

You will help develop AI tools that analyze pavement imagery, automate engineering workflows, build AI agents, retrieve knowledge from large document collections, and support next-generation digital products. Projects include computer vision, big language models (LLMs), RAG, GIS integration and edge AI deployment.