Job Description

General Responsibilities:

We are looking for a hands-on AI Engineering Intern who has already built real projects and wants 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, large language models (LLMs), retrieval-augmented generation (RAG), GIS integration, and edge AI deployment.

Essential Roles and 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

Requirements

• Pursuing BS/MS in: Computer Science Artificial Intelligence Machine Learning Data Science Robotics Computer Engineering Related field Strong Python experience Experience with at least one: PyTorch TensorFlow Ultralytics YOLO Detectron2 HuggingFace Experience using LLMs beyond prompting