Machine Learning Analyst

About the Role

Sobeys is looking for a Machine Learning Analyst to join its MLOps Engineering team within Enterprise Data and Advanced Technologies. Based at the Sobeys COLAB Office in downtown Toronto, this role supports the design, delivery, and improvement of scalable AI/ML and agentic systems that help transform retail operations and customer experiences across Canada.

You will work with a multidisciplinary group of data scientists, engineers, developers, architects, and analysts focused on building measurable, production-ready solutions that improve customer engagement, sales growth, and profitability.

What You Will Do

• Analyze complex business workflows and translate them into practical AI-driven solutions that create measurable impact.
• Develop and support Langgraph-based agentic applications that use LLMs and tool integrations to automate business tasks.
• Build, maintain, and improve MLOps and LLMOps workflows for model training, testing, deployment, and monitoring.
• Create scalable data pipelines with PySpark, including UDF development and performance tuning in distributed environments.
• Write clean, modular, and testable Python code using object-oriented design principles.
• Collaborate with data scientists, data engineers, analysts, product managers, and business stakeholders to deliver AI-enabled capabilities.
• Learn and work within the Snowflake ecosystem to support business-facing agentic solutions.
• Contribute as a strong team player with a hands-on mindset and a willingness to learn.

What We Are Looking For

• A bachelor’s degree or higher in Computer Science, Software Engineering, Data Science, or a related field.
• Experience implementing MLOps and LLMOps engineering systems.
• At least 1 year of professional experience with object-oriented Python and production-grade software design patterns.
• At least 1 year of experience working with Spark, PySpark or Scala, including efficient pipeline development and optimized UDFs.
• At least 1 year of experience supporting or debugging production ML pipelines.
• Working knowledge of MLOps tools and frameworks such as MLflow.
• Understanding of vector databases such as FAISS, Pinecone, or Weaviate, along with retrieval methods like RAG.
• Experience balancing multiple stakeholders, workstreams, priorities, and deadlines in a fast-paced environment.
• Strong communication skills with the ability to explain technical topics to both technical and non-technical audiences.
• Prior production deployment experience with LLMs or fine-tuned models is considered an advantage.
• Exposure to cloud platforms such as AWS, GCP, Azure, or Databricks is strongly preferred.

About Sobeys

Sobeys is one of Canada’s leading grocery retailers, operating more than 1,600 stores across all 10 provinces under banners such as Sobeys, Safeway, IGA, Foodland, FreshCo, Thrifty Foods, and Lawtons Drug Stores. The company’s 128,000 teammates and franchise affiliates are dedicated to serving customers and communities with great food and excellent experiences.

Total Rewards

Depending on the role and eligibility, team members may receive health and dental coverage, retirement and savings programs including an Employee Share Ownership Plan, a 10% in-store discount at participating banners, virtual healthcare, an Employee and Family Assistance Program, learning and development opportunities, parental leave top-up, and paid vacation.

Sobeys states that its compensation approach is intended to be flexible, fair, and competitive. The exact pay is determined based on qualifications, experience, and internal equity, and the company notes that the compensation range may be shared where required by pay transparency rules.

Additional Information

Sobeys may use artificial intelligence tools to help streamline candidate screening, assessments, and recruitment tasks, but hiring decisions are made by the company’s hiring teams.

Applicants who need accommodation due to a disability can request support at any stage of the hiring process. The company emphasizes an accessible and inclusive recruitment experience.

External websites may republish this posting and may show compensation estimates based on comparable jobs and market data; these figures are for general reference only and are not verified by Sobeys.

Successful candidates must provide documentation confirming their legal right to work in the position before starting employment.

Sobeys requests that staffing agencies do not call or send unsolicited resumes.

Candidate Communication

Only candidates selected for interviews will be contacted.