Machine Learning Engineer

Sobeys; Toronto; Hybrid; CAD 120,000 - 155,000; Full time

Job summary

Sobeys is seeking a Machine Learning Engineer to join the Enterprise Data and Advanced Technology team in a hybrid role at Sobeys COLAB Office in Toronto. The role focuses on building LangGraph-based agentic systems, advanced Python development, and ML Ops to deploy scalable AI/ML solutions that impact Sobeys’ customer experience and business operations.

You will collaborate with data scientists, engineers, analysts, and product managers to deliver intelligent, production-grade ML features,

Qualifications

• Bachelor’s degree in Computer Science or Software Engineering (or equivalent) with relevant AI/ML focus.
• Experience designing agentic AI systems and production-grade Python software is required.
• Proven track record with LangGraph/LLM-driven agents and ML Ops tooling.

Responsibilities

• Develop end-to-end Agentic AI/ML solutions and maintain scalable systems.
• Build Lang chain-based agentic applications using LLMs and tool integrations.
• Design modular, testable Python data/ML code with OO principles.
• Collaborate with data scientists, engineers and product stakeholders to deliver ML features.

Skills

LangGraph

Object-Oriented Python

ML Ops

Data-driven analysis

Communication

Education

Bachelor’s degree in CS/Software Engineering

Tools

MLflow

Databricks

Snowflake

FAISS

Job description

Job Title: Machine Learning Engineer

Location: Sobeys COLAB Office (Toronto Downtown)

Team: Enterprise Data and Advanced Technology

Overview

The Enterprise Data and Advanced Technology team at Sobeys operates on the frontlines of retail innovation. We are a multi-disciplinary team of data scientists, engineers, software developers, architects, and analysts who design, develop, and deploy high-impact, scalable measurement for AI/ML products and services that are fundamentally transforming how Sobeys and its family of banners interact with customers and operate their businesses. We leverage the latest cloud technology and advanced analytical techniques to connect the dots between customer behaviour and business operations and unearth the true drivers of customer engagement, sales growth, and profitability. Our work directly impacts the daily lives of millions of Canadian consumers and is a key pillar in our mission to become the #1 retail brand in Canada.

What you’ll get to do in this role:

We are seeking a highly capable Machine Learning Engineer with deep expertise in building Lang graph based agentic systems, Object-Oriented Python, and ML Ops. In this role, you will develop and maintain end-to-end Agentic AI/ML solutions, research complex business processes, and build intelligent systems that are scalable, maintainable, and impactful.

Key Responsibilities:

• Agentic Engineer: Ability to understand the business process and data science, operations research algorithms to develop conversational / process automation agents. Bring most latest advancements of agentic engineering to the business benefit with rapid development.
• Lang chain/Lang graph Agent Development: Build and maintain Lang chain-based agentic applications using LLMs and tool integrations to automate and optimize business tasks.
• Object-Oriented Python Development: Design maintainable, modular, and testable ML and data engineering codebases using object-oriented principles.
• Cross-Functional Collaboration: Work closely with Data Scientists, Data Engineers, Analysts, Product Managers, and other business stakeholders to deliver impactful AI-driven features and tools.

#LI-Hybrid

What you should bring to the team:

• Bachelor’s or above degree in Computer Science, Software Engineering Architecture, Agentic AI Engineering research - certifications.
• Proven multiple implementation experience with LangGraph and developing LLM-driven compound agentic system.
• 4+ years of industry level expertise in Object-Oriented Python development with production-grade software design patterns in the industry.
• Proficiency in MLOps tools and frameworks (e.g., MLflow, Databricks, Snowflake).
• Solid understanding of vector databases (e.g., FAISS, Databricks Vector Search) and LLM retrieval techniques (e.g., RAG).
• Proven experience managing multiple stakeholders, concurrent workstreams, priorities and deadlines in a high pressure, fast-paced environment
• Excellent communication skills, with the ability to explain and present complex technical concepts to both technical and non-technical audiences
• Experience deploying LLMs or fine-tuned models in production environments is a significant asset.
• Familiarity with cloud platforms (Azure preferred, GCP, AWS) is strongly recommended.
• Having experience leading AI/ML projects or mentoring junior engineers would be looked at with priority.
• Knowledge of enterprise data architecture and ML system design would be a great asset.