Machine Learning Engineering Co-op (8 months)

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 environment with three days per week in office