Machine Learning Engineer Intern (Work-Study Only)

Note: This position is only open to students who qualify for federal or state work-study.

As a Machine Learning Engineer Intern at Folio, you will support the development, evaluation, and improvement of models that help students connect with meaningful, career-aligned opportunities. You will work with real product and engagement data to prototype models, build pipelines, and explore ways to enhance matching, recommendations, and user insights.

This role is ideal for students studying data science, computer science, statistics, or related fields who want hands-on experience applying machine learning techniques in a practical and mission-driven setting.

What You’ll Do

Assist in building, testing, and refining machine learning models and data pipelines.

Work with datasets related to user activity, program participation, and platform engagement.

Support feature engineering, model evaluation, and experiment tracking.

Help document findings, model performance, and recommendations.

Collaborate with the data, product, and engineering teams to integrate insights into real product improvements.

What You’ll Gain

Practical experience applying machine learning methods to real-world datasets.

Exposure to tools such as Python, SQL, Jupyter notebooks, and ML libraries including scikit-learn, pandas, or TensorFlow depending on your background.

Mentorship from data and engineering professionals familiar with model development and evaluation.

Insight into how machine learning informs product decisions in education and workforce development.

A meaningful way to use your work-study hours by contributing to student-focused data innovation.

Qualifications

Must be eligible for federal or state work-study funding.

Currently pursuing a degree in Data Science, Computer Science, Statistics, or a related field.

Familiarity with Python and basic machine learning concepts.

Comfort working with data through libraries such as pandas or NumPy.

Strong problem-solving and analytical skills.

Interest in applied machine learning, model evaluation, or student-oriented technology.