AI & Data Science Intern

Posted 23 Days Ago
Carlisle, PA, USA
In-Office
Internship
Industrial • Manufacturing
The Role
Support development of agentic AI workflows, backend APIs, and interactive prototypes. Work on computer vision (SEM image analysis), data wrangling, statistical modeling, and machine learning models. Document reproducible code, present results, and stay current with AI tools to accelerate materials R&D.
Summary Generated by Built In
Job Summary & Responsibilities

The AI & Data Science Engineering Intern will support cutting-edge projects at the intersection of software engineering, applied AI, and materials innovation. The intern will work on initiatives that combine agentic AI workflows, computer vision, and data science to accelerate research and development in construction materials. The role includes building end-to-end prototypes that integrate backend services, AI models, and user interfaces to drive digital transformation across the organization.

Duties and 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.

Qualification:

  • 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.

Additional Information:

Work Location: Carlisle, PA.  No travel required. Remote work is not available for this position.

#LI-BR1

Skills Required

  • Currently pursuing a Master's or PhD in Computer Science, Data Science, Engineering, or related field with a minimum 3.0 GPA
  • Strong programming skills in Python
  • Experience with libraries such as pandas, scikit-learn, OpenCV, TensorFlow or PyTorch
  • Experience with backend frameworks (FastAPI, Flask, Django)
  • Experience with 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
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The Company
5,900 Employees
Year Founded: 1917

What We Do

Carlisle Companies Incorporated is a leading supplier of innovative building envelope products and solutions designed to make buildings more energy efficient and resilient. Through its Construction Materials (CCM) and Weatherproofing Technologies (CWT) segments, the company manufactures and sells high-performance roofing, insulation, and waterproofing systems for the commercial and residential building industries globally.

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