Applied Data Science Intern – Generative AI
Ricoh Canada Production Print is an integrated solutions provider that empowers digital workplaces through innovative technology and services. They are looking for a Data Science Intern to focus on Generative AI during Summer 2026, where the intern will work with large datasets and apply advanced AI techniques to contribute solutions with real-world impact.
Responsibilities
- Develop, fine-tune, and evaluate generative AI and large language models using AWS frameworks and platforms
- Analyze multimodal datasets (machine telemetry, service data, documentation, unstructured text, and internal knowledge systems) to derive insights and support decision-making
- Design retrieval-augmented generation (RAG), summarization, and recommendation solutions that connect across multiple data sources
- Apply Model Context Protocol (MCP) and design agentic workflows that allow LLMs to interact seamlessly with diverse enterprise systems and autonomously perform multi-step tasks
- Collaborate with cross-functional teams to ensure models can be deployed in cloud-based workflows
- Present research findings, prototypes, and results to technical and business stakeholders
Skills
- Student must be currently enrolled in an accredited college or university or enrolled to continue their education in an accredited graduate program
- Students must have a cumulative GPA of 3.0 or higher
- Students are to successfully complete all required screenings prior to hire
- Currently enrolled student in Data Science, Computer Science, Electrical/Computer Engineering, Applied Mathematics, or a related field
- Strong background in machine learning, natural language processing, and/or deep learning
- Proficiency in Python and modern ML/AI frameworks
- Familiarity with cloud-based machine learning platforms (AWS preferred)
- Strong analytical and problem-solving skills
- Master's-level student (PhD candidates also welcome)
- Prior research or project experience with generative AI
- Experience working with large, heterogeneous datasets
- Exposure to data engineering concepts (ETL, feature engineering, pipeline development)
- Knowledge of agentic AI systems or standards such as Model Context Protocol (MCP)
- Publication record, open-source contributions, or demonstrable project portfolio
Education Requirements
- Working towards - B.S., M.S., or PhD. degree in Computer Science, Computer Engineering, or a related field
- Master’s-level student (PhD candidates also welcome)
Benefits
- Choose from a broad selection of medical, dental, life, and disability insurance options.
- Contribute to your financial security with Retirement Savings Plan (401K), Health Savings Account (HSA), and Flexible Spending Account (FSA) investments.
- Augment your education with team member tuition assistance programs.
- Enjoy paid vacation time and paid holidays annually
- Tap into many other benefits to enhance your health, wellness, and ongoing personal and professional development.
Company Overview