Start Early. Grow for a Lifetime. A co-op student role at Sobeys is more than just a work term. It is your own personal journey in discovering how Sobeys operates, gaining valuable insights and relevant experience in your field of study, networking with experienced professionals, and obtaining first-hand exposure to one of Canada’s largest grocers.

Most importantly, you will have an opportunity to work alongside some of the most talented people in the grocery business. We believe that the best ideas come from a diverse workforce with unique perspectives and encourage our co-op students to be curious and innovative. This is an outstanding opportunity to join a leading Canadian company with a clear vision and focus.

As a Machine Learning Engineering Co-op Student, you will be responsible for contributing to advanced data, machine learning, and generative AI initiatives that support real business outcomes across the organization. Here's where you'll be focusing Agentic engineering: Build and maintain LLM-based agentic applications using frameworks such as LangGraph and LangChain, integrating tools to automate complex workflows MLOps and LLMOps: Support the development of automated pipelines for training, testing, deploying, and monitoring ML models and agents using MLflow Data engineering: Create scalable data processing pipelines using PySpark within Databricks and Snowflake environments ML implementation: Implement and optimize traditional machine learning algorithms alongside generative AI techniques to solve business challenges Business collaboration: Partner with business stakeholders to contribute to production systems that impact stores nationwide This role is accountable for: Execution: Delivering high-quality, scalable AI and data solutions Innovation: Applying modern AI, ML, and agent-based approaches to real-world problems Collaboration:



Working effectively across technical and business teams Reliability: Supporting stable and monitored production systems What you have to offer Education: Currently pursuing a degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical discipline Mindset: Curiosity for solving problems, strong execution drive, and enthusiasm for emerging technologies Communication: Strong communication skills with a collaborative, team-first approach AI experience: Hands-on experience with agentic AI using frameworks such as LangGraph or LangChain and tools like MLflow Data engineering: Practical experience building scalable solutions using PySpark, SQL, Scala, or similar languages ML foundations: Understanding of traditional machine learning algorithms and core data structures Programming: Strong object-oriented programming skills Version control: Experience using Git for collaboration and code management Nice to have: Exposure to Spark, Databricks Asset Bundles, vector databases, RAG, FAISS, Streamlit, Databricks, Snowflake, or Azure DevOps/Pipelines What we have to offer Real-world experience: Work on production systems that directly impact stores and operations nationwide Hands-on learning: Build and deploy real AI, ML, and data engineering solutions Mentorship: Learn from experienced engineers and data professionals Exposure across the business: Collaborate with stakeholders across technical and business domains Skill development: Strengthen capabilities in AI, ML, data engineering, and modern development tools The right tools: Access to leading tools such as Claude, GitHub Copilot, Genie, Cortex, and more Future opportunities: Build experience that can lead to future roles within Sobeys Team culture: Monthly socials, food and chess clubs, and seasonal table tennis tournaments Work model: Hybrid workplace with three days per week in office

📌 Machine Learning Engineering Co-op (8 months) (Toronto)
🏢 Sobeys
📍 Toronto