Digital Innovation Intern

Ingredion Incorporated
Bridgewater, New Jersey, United StatesPosted Sep 1, 2026
Summer 2027

About the role

About Ingredion

Join Ingredion, where innovation impacts lives worldwide! Without even realizing it, you’ve experienced our work in your favorite chocolate, your pet’s food, the paper you write on, and your everyday snacks. As a global powerhouse across more than 60 industries, we harness the potential of natural ingredients to transform lives. Whether you’re just starting your career or bringing years of experience, there's a place for you here to make a real difference. Be part of our team that values a wide range of perspectives and is committed to shaping a better world with every product we create. Location: Bridgewater, NJ Workplace type: Hybrid (3 days/week on-site) We have an exciting opportunity for an ambitious student to join our R&D team for summer 2027! As the Digital Innovation Intern, you will help accelerate the adoption of predictive formulation and digital innovation capabilities across our organization. Working closely with formulation scientists and digital innovation leaders, you will explore leading academic approaches and develop practical digital tools for automated data capture, data quality assessment, feature extraction, predictive modeling, and virtual experimentation. Your work may include converting food or microscopy images into quantitative measurements, creating machine-learning descriptors from molecular structures, developing AI-powered workflows, and applying large language models (LLM) and agentic approaches to scientific data analysis and knowledge extraction!

What you will do

Review academic literature, open-source methods, and emerging technologies relevant to predictive formulation, machine learning, artificial intelligence, agentic systems, automated data capture, image analysis, and computational chemistry. Develop digital tools that automate data capture, data quality assessment, feature extraction, data preparation, and model development workflows. Build predictive models and create virtual experiment tools that allow s

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