Machine Learning Engineer
Requisition ID: 189427
Career Group: Corporate Office Careers
Job Category: Engineering Machine Learning Operations
Travel Requirements: 0 - 10%
Job Type: Full-Time
Country: Canada (CA)
Province: Ontario
City: Toronto
Location: Sobeys Innovation Hub
Embark on a rewarding career with Sobeys Inc., celebrated among Canada’s Top 100 employers, where your talents contribute to our commitment to excellence and community impact.
Our family of 128,000 employees and franchise affiliates share a collective passion for delivering exceptional shopping experiences and amazing food to all our customers. Our mission is to nurture the things that make life better – great experiences, families, communities, and our employees. We are a family nurturing families.
A proudly Canadian company, we started in a small town in Nova Scotia but we are now in communities of all sizes across this great country. With over 1,600 stores in all 10 provinces, you may know us as Sobeys, Safeway, IGA, Foodland, FreshCo, Thrifty Foods, Lawtons Drug Stores or another of our great banners but we are all one extended family.
Ready to Make an impact?
Job Title: Machine Learning Engineer
Location: Sobeys COLAB Office (Toronto Downtown)
Team: Advanced Analytics
Overview
The Advanced Analytics 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.
Here’s where you’ll be focusing:
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, PySpark, Object-Oriented Python, and ML Ops. In this role, you will develop and maintain end-to-end Gen AI/Traditional ML solutions, research complex business processes, and build intelligent systems that are scalable, maintainable, and impactful. You'll also play a key role in maintaining robust Data Ops and ML Ops pipelines for continuous model improvement and reliability.
Key Responsibilities:
- 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.
- End-to-End ML Project Ownership: Lead the full lifecycle of ML projects, from scoping and prototyping through deployment, monitoring, and iterative improvement.
- Business Process Research: Analyze and translate complex business operations into technical AI solutions with measurable value.
- PySpark & Data Pipeline Development: Create scalable data processing pipelines using PySpark, including UDF creation and performance tuning across distributed systems.
- Object-Oriented Python Development: Design maintainable, modular, and testable ML and data engineering codebases using object-oriented principles.
- ML Ops & Data Ops: Build and maintain automated workflows for training, testing, deployment, and monitoring of ML models using industry-standard ML Ops and Data Ops tools.
- 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 #LI-VJ1
What you have to offer:
What you should bring to the team:
- Bachelor’s or above degree in Computer Science, Software Engineering, AI.
- Proven multiple implementation experience with LangGraph and developing LLM-driven compound agentic system.
- 5+ years of industry level expertise in Object-Oriented Python development with production-grade software design patterns in the industry.
- 5+ years of industry level experience with Spark (using PySpark or Scala), including building efficient data pipelines and writing optimized UDFs.
- 5+ years of industry level experience in maintaining/debugging production level ML pipelines
- Proficiency in MLOps tools and frameworks (e.g., MLflow).
- Familiarity with DataOps (Airflow preferred) practices for managing large-scale, reliable data workflows.
- 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.
At Sobeys we require our teammates to have the ability to adhere to a hybrid work model that requires your presence at one of our office locations at least three days per week. This requirement is integral to our commitment to team collaboration and the overall success of our office culture.
We offer a comprehensive Total Rewards package, which varies by role and designed to help our teammates to live better – physically, financially and emotionally.
Some websites share our job opportunities and may provide salary estimates without our knowledge. These estimates are based on similar jobs and postings for general comparison, but these numbers are not provided by our organization nor monitored for accuracy.
We will consider factors such as your working location, work experience and skills as well as internal equity, and market conditions to ensure the selected candidate is paid fairly and competitively. We look forward to discussing the specific compensation details relevant to this role with candidates who are selected to move forward in the recruitment process.
Our Total Rewards programs, for full-time teammates, goes well beyond your paycheque:
- Competitive Benefits Package, tailored to meet your needs, including health and dental coverage, life, short- and long-term disability insurance.
- Access to Virtual Health Care Platform and Employee and Family Assistance Program.
- A Retirement and Savings Plan that provides you with the opportunity to build and add value to your savings.
- A 10% in-store discount at our participating banners and access to a wide range of other discount programs, making your purchases more affordable.
- Learning and Development Resources to fuel your professional growth.
- Parental leave top-up
- Paid Vacation and Days-off
We are committed to accommodating applicants with disabilities throughout the hiring process and will work with applicants requesting accommodation at any stage of this process.