Machine Learning & Software Engineer Intern (Summer 2025)

Overview

At Ntrepid, we build mission-critical products that empower our customers online operations. Our Machine Learning Research and Development team is seeking a talented Machine Learning and Software Engineering Intern for summer of 2025. This is an opportunity to contribute to impactful projects while sharpening your technical skills and collaborating with seasoned professionals.

 

We’re looking for an individual with a strong foundation in programming (especially Python), a passion for data science or machine learning, and a knack for creative problem-solving. As an intern, you’ll work alongside our team to develop, test, and release business-critical software products, gaining experience in both machine learning research and production-grade software development. The opportunity is based out of our Herndon, Virginia office with a flexible hybrid work schedule.

Responsibilities

• Collaborate with engineers in a cross-functional team to design, develop, test, and release software and systems components.
• Work on challenging machine learning and data science projects in collaboration with our researchers.
• Contribute to the definition of work.
• Write all levels of automated tests (e.g., unit, integration, system) to ensure the quality and documentation of the delivered product.
• Learn about designing for security and vulnerability mitigation.
• Contribute to all forms of documentation.

Qualifications

• U.S. Citizenship required.
• Pursuing a degree in Machine Learning, Data Science, Computer Science, Mathematics, Engineering, or a related field.
• Experience writing code in Python.
• Basic knowledge of statistics.
• Basic knowledge of relational databases.
• Excellent written and verbal skills to communicate with technical team members and managers.
• Knowledge of software development lifecycle.

 

Preferred Qualifications

• Experience using Git.
• Experience with ML research (i.e., model development, dataset building, and evaluation).
• Knowledge of software engineering best practices.
• Knowledge of common data structures and algorithms.