Machine Learning Intern — Evaluation & Retrieval Systems (Summer 2026)

Toronto / Remote (Canada) We are looking for a **Machine Learning Intern** to work on evaluation and retrieval systems for document workflows in regulated environments. This role focuses on **experimental design, model behavior analysis, and reliability under real-world constraints** . The work sits at the intersection of applied ML research and early-stage system development. You will work on problems such as: • Designing experiments to analyze **model reliability and edge cases** • Evaluating **retrieval strategies for document-style data** • Building **evaluation and regression testing pipelines** • Generating **synthetic document scenarios to stress-test assumptions** This role is well suited for students who enjoy **structured thinking, experimentation, and understanding system behavior** , not just model training. **Background** • 3rd–4th year undergraduate in CS / AI / Data Science or similar • Strong Python skills • Interest in experimentation, robustness, and reproducibility **Details** • Summer 2026 (12–16 weeks) • Paid internship • Co-op / internship (full-time) • Toronto preferred, remote across Canada possible Because LinkedIn generates a high volume of low-signal applications, **LinkedIn applications will not be reviewed.** Please apply using the form below: https://tinyurl.com/multiplaiinternshipsummer