AI and Machine and Learning Intern

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AI and Machine and Learning Intern

Imperial Distributors

icon Worcester, MA, US, 01607

iconIntern

icon31 January 2026

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Position Summary

We are seeking a highly motivated AI and Machine Learning Intern to join our Data Team. This internship offers a unique opportunity to apply advanced analytical and machine learning skills to solve real-world business challenges using actual company data. The intern will work closely with the team to develop and train AI-driven solutions aimed at improving business operations, ranging from building intelligent chatbots to enhancing distribution center slotting strategies.

Key Responsibilities

  • Champion designing, building, and training machine learning models using organizational data
  • Contribute to the development of an AI-based chatbot to provide instantaneous answers to company questions
  • Apply machine learning techniques to optimize operational challenges such as slotting and inventory management in the distribution center
  • Collaborate with IT, Data, Warehouse, and business stakeholders to gather requirements and validate solutions
  • Research and recommend AI/ML tools and frameworks to support development efforts
  • Analyze and visualize data to uncover patterns and support model training and validation
  • Document models, processes, and results for future reference and scalability
  • Other duties and tasks as assigned

Learning Objectives

  • Gain hands-on experience developing AI and machine learning solutions with real business impact
  • Apply academic knowledge to real-world datasets and operational challenges
  • Strengthen skills in data preparation, model development, and performance evaluation
  • Understand how AI and ML integrate into business workflows and decision-making
  • Collaborate in a professional, cross-functional environment working closely with IT, Distribution, and Business Leadership

Additional Information

  • This is a paid internship at a rate of $18.00 per hour.
  • Internship runs for 12 weeks, 20 hours per week.
  • The role may involve a combination of on-site and remote work, depending on project needs,  with required in-person attendance for onboarding, team meetings, and trainings.