AI & Data Science Intern

Summary

Carlisle Construction Materials is seeking an AI & Data Science Engineering Intern to support innovative projects at the intersection of software engineering, applied AI, and materials innovation. The intern will work on initiatives that integrate AI workflows, computer vision, and data science to drive digital transformation in construction materials.

Responsibilities

• Assist in the design and development of agentic AI workflows, integrating large language models with data sources and multi-agent orchestration
• Develop and maintain backend APIs and services using frameworks such as FastAPI to support AI and data science applications
• Build interactive dashboards and prototypes with Streamlit, Reflex, or similar tools for internal stakeholders
• Contribute to computer vision workflows, such as SEM image analysis and defect detection, to automate materials characterization
• Perform data wrangling, exploratory analysis, and statistical modeling to uncover insights from experimental, operational, and customer datasets
• Collaborate with the team to design, implement, and test machine learning models (regression, clustering, NLP, computer vision)
• Document methodologies, maintain reproducible codebases, and present results to both technical and business stakeholders
• Stay current with emerging tools, frameworks, and best practices in agentic AI, software engineering, computer vision, and data science

Skills

• Currently pursuing a Master's or PhD in Computer Science, Data Science, Engineering, or a related field from an accredited university with a minimum 3.0 GPA
• Strong programming skills in Python with experience in libraries such as pandas, scikit-learn, OpenCV, TensorFlow/PyTorch
• Experience with backend frameworks (FastAPI, Flask, Django) and frontend/UI tools (Streamlit, Reflex, React-based)
• Familiarity with LLMs, agentic AI frameworks, or orchestration tools (LangChain, LlamaIndex, or custom pipelines)
• Solid understanding of machine learning and computer vision principles
• Interest in applying AI/ML to industrial and materials science challenges

Qualifications

Must Haves

• Currently pursuing a Master's or PhD in Computer Science, Data Science, Engineering, or a related field from an accredited university with a minimum 3.0 GPA
• Strong programming skills in Python with experience in libraries such as pandas, scikit-learn, OpenCV, TensorFlow/PyTorch
• Experience with backend frameworks (FastAPI, Flask, Django) and frontend/UI tools (Streamlit, Reflex, React-based)
• Familiarity with LLMs, agentic AI frameworks, or orchestration tools (LangChain, LlamaIndex, or custom pipelines)
• Solid understanding of machine learning and computer vision principles
• Interest in applying AI/ML to industrial and materials science challenges