AI Intern

GAF•Parsippany, NJ

11d

About The Position

At GAF, we cover more than just buildings. We cover each other. Under this roof, you will have the tools and resources you need to begin, grow, and develop in your career. Under this roof, you will experience our incredible culture and be empowered to support your teammates, your customers and especially your community through collaboration. Under this roof, we define the future while leading the present through our commitment to continuous improvement and never being satisfied with the status quo. We are GAF. And under this roof, we protect what matters most. Put your classroom studies into practice in the real world and gain the experience to help determine your journey after graduation. At GAF, we’ll make sure you get going on your very first day with a comprehensive orientation into our company. In our program, you will have the opportunity to own your own projects, participate in meetings, and work cross-functionally with other departments. GAF is looking for a Data Science (AI) Intern. The ideal candidate for this role is majoring in Computer Science, Data Science, Statistics, Mathematics, or a related Engineering field with a focus on Artificial Intelligence. This intern will assist with the development, testing, and deployment of machine learning models and AI solutions (including predictive analytics and generative AI) within GAF's data ecosystem. Leveraging tools such as Python, Google Cloud Platform (GCP), and modern ML frameworks, the intern will have a great deal of opportunity to learn, contribute to real-world AI initiatives, and develop leadership skills.

Requirements

Pursuit of a Bachelor’s or Master's Degree from an accredited institution in a quantitative field, with a minimum overall GPA of 3.0, preferably with a sophomore standing.
Business Analysis & Process Mapping: process modeling techniques and tools to clearly map current states, future states, and decision trees.
Applied AI Literacy: Conceptual understanding of Generative AI capabilities, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic workflows, including their limitations (e.g., hallucinations, context windows).
Prompt Engineering & Prototyping: Drafting, testing, and refining system prompts to validate business use cases before handing them off for full-scale software development.
Cross-Functional Communication: clearly communicating with the business users on their needs
Requirements Gathering & Documentation: Writing detailed, robust technical documentation and acceptance criteria.
AI Build: Develop and prototype AI/ML solutions for specific business needs using Python, standard ML libraries (e.g., scikit-learn, TensorFlow, PyTorch), and Google Cloud Platform.

Nice To Haves

Experience or familiarity with Generative AI APIs (e.g., OpenAI, Google Gemini) and prompt engineering.
Familiarity with version control systems (e.g., Git) and MLOps concepts.
Excellent communication and presentation skills.
A rigorous approach to code quality, model evaluation, and data integrity.

Responsibilities

Collaborate directly with business stakeholders and operational teams to deeply understand their daily workflows, pain points, and strategic objectives.
Evaluate existing business operations to determine if they are viable candidates for Generative AI or Agentic integration, weighing potential efficiency gains against technical feasibility and risk.
Act as the critical bridge between business units and AI developers, converting complex business logic into clear technical requirements, user stories, and AI models.
Define success metrics for newly implemented AI workflows, monitoring user adoption, mitigating workflow bottlenecks, and ensuring the AI solution actually solves the intended business problem.