2025 TRAC Summer Internship Program – (Artificial Intelligence Engineering)

Location: Princeton, NJ (Hybrid) – 3 days in-office/2 days from home

Are you looking for an opportunity to apply your skills and course learnings in a professional setting while also developing strong business relationships, work on challenging projects, receive mentoring from industry experts, and take part in exciting group activities?  Then TRAC Intermodal’s 2025 TRAC Summer Internship Program is the ideal spot for you next summer!

We are currently accepting applications for rising juniors and seniors for participation in our paid, 11-week summer internship program centrally located at TRAC Intermodal’s corporate headquarters in Princeton, NJ.

About TRAC

TRAC is a leading chassis provider in North America helping to facilitate the movement of goods from coast to coast.  We have built our brand by staying true to our roots while always being at the forefront of industry change.  TRAC Team Members are the key to our success.  We embrace and encourage our employees to bring their true and authentic selves in addition to their personal best to work every day.

Your Role

We are seeking a motivated AI Engineer Intern who is passionate about machine learning, data analysis, and AI-driven innovation. In this role, you’ll gain hands-on experience in building, optimizing, and deploying AI models. You will work closely with our data and engineering teams to deliver solutions that enhance TRAC’s various applications.

What You’ll Do

Core day-to-day responsibilities may include but are not limited to any of the following:

• Model Development: Assist in developing, training, and testing machine learning models for various applications, including classification, prediction, and natural language processing.
• Data Preparation: Collaborate on data collection, cleaning, and preprocessing to ensure data quality and prepare it for machine learning pipelines.
• Feature Engineering: Identify and create meaningful features from raw data to improve model accuracy and performance.
• Model Optimization: Experiment with hyperparameters, fine-tune algorithms, and explore methods to enhance model efficiency.
• Performance Evaluation: Use metrics to evaluate model performance and suggest improvements based on results.
• Collaboration: Work closely with AI engineers, data scientists, and product teams to understand project requirements and translate them into effective AI solutions.
• Documentation: Document processes, code, and model findings to ensure knowledge-sharing and reproducibility.

Required Qualifications

• Enrolled as Rising Junior or Senior in an accredited college or university seeking a degree in Systems Engineering, Computer Science, Data Science, Machine Learning, or a related field.
• 0 grade point average or higher
• Strong record of academic performance and extracurricular/community involvement
• Programming Skills: Proficiency in Python; familiarity with libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch.
• Data Handling: Knowledge of data preprocessing, feature engineering, and handling large datasets.
• Problem-Solving Abilities: Analytical and solution-oriented with a strong interest in tackling real-world AI challenges.
• Communication Skills: Ability to clearly communicate technical information to both technical and non-technical team members.
• Bonus Skills: Familiarity with Azure, MLOps tools or database querying (SQL).
• This role is intended for candidates who are eligible to work in the United States without further sponsorship or authorization upon completing their education.

Timeline

The internship program will run from Monday, June 2nd thru Friday, August 15th, 2025.

We review applications on a rolling basis, and we encourage you to apply as soon as you are ready.

All applications should be fully completed by February 14th, 2024, at midnight ET.

Our Application Process:

1. Submit your application.
2. Receive invitation for a video interview with our Talent Acquisition team.
3. If selected to advance, receive invitation for one or more interviews (either in-person or video) with the department manager and mentor.