AI Intern

GAF•Parsippany, NJ

1d•Onsite

About The Position

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.
Academic, project, or internship experience focusing on Machine Learning, Artificial Intelligence, Deep Learning, or Natural Language Processing (NLP).
Strong programming proficiency in Python or R, and hands-on experience with SQL.
Experience working with structured and unstructured data for model development.
Ability to communicate complex mathematical and computational concepts with clarity and precision.

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

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.
Assist in training, validating, and fine-tuning predictive models and/or Large Language Models (LLMs) to optimize manufacturing, supply chain, or customer experience processes.
Analyze complex datasets to engineer new features and generate insights that support the development of AI-driven products.
Present project milestones and model results at monthly Data Science meetings to a cross-functional group of analysts and engineers.
Collaborate with data engineers to help build and optimize data pipelines required for training and deploying AI models.
Deliver complex technical insights and model predictions in a clear, digestible manner to non-technical business stakeholders.
Stay current with emerging AI trends, tools, and methodologies, recommending innovative approaches to the team.