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About the Role

The MLOps Engineering team of Advanced Technologies operates on the frontlines of retail innovation, designing, developing, and deploying scalable measurement for AI/ML products and services that transform customer interaction and business operations. This role is crucial in leveraging cloud technology and advanced analytics to understand customer behavior and drive business growth, impacting millions of Canadian consumers.

Responsibilities

Deliver, maintain, and improve end-to-end MLOps/Agentic solutions.
Research complex business processes and build scalable, maintainable, and impactful intelligent systems.
Build and maintain Langgraph-based agentic applications using LLMs and tool integrations.
Build and maintain automated workflows for training, testing, deployment, and monitoring of ML models using MLOps and LLMOps tools.
Create scalable data processing pipelines using PySpark, including UDF creation and performance tuning.
Design maintainable, modular, and testable ML and data engineering codebases using object-oriented principles.
Collaborate with Data Scientists, Data Engineers, Analysts, Product Managers, and business stakeholders.
Learn the Snowflake environment and deliver business-facing agentic solutions within that platform.

Requirements

Proven implementation experience with MLOps engineering systems and LLMOps systems.
1+ years of industry-level expertise in Object-Oriented Python development with production-grade software design patterns.
1+ years of industry-level experience with Spark (PySpark or Scala), including building efficient data pipelines and writing optimized UDFs.
1+ years of industry-level experience in maintaining/debugging production-level ML pipelines.
Solid understanding of vector databases (e.g., FAISS, Pinecone, Weaviate) 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 (AWS, GCP, Azure, Databricks) is strongly recommended.
Successful candidates will be required to provide documentation to prove their legal ability to work in the position.

Skills

Machine Learning Engineering
MLOps
Langgraph
Agentic LLMOps
Object-Oriented Python
PySpark
Databricks
MLOps tools (e.g., MLflow)
Vector databases (e.g., FAISS, Pinecone, Weaviate)
LLM retrieval techniques (e.g., RAG)
Cloud platforms (AWS, GCP, Azure, Databricks)

Location

Sobeys COLAB Office (Toronto Downtown)

Work Type

Full-time

Experience Level

1+ years of industry level expertise

Education Level

Bachelor’s or above degree in Computer Science, Software Engineering, Data Science
LLMOps engineering certifications

Benefits

Health and dental benefits
Retirement and savings programs including an Employee Share Ownership Plan
10% in-store discount at participating banners
Virtual healthcare
Employee and Family Assistance Program
Learning and development opportunities
Parental leave top-up
Paid vacation

About the Company

Sobeys Inc. is celebrated among Canada’s Top 100 employers.
Sobeys is one of Canada’s leading grocery retailers, with more than 1,600 stores across all 10 provinces and banners including Sobeys, Safeway, IGA, Foodland, FreshCo, Thrifty Foods, and Lawtons Drug Stores.
Our 128,000 teammates and franchise affiliates are passionate about delivering great food and exceptional experiences to our customers and communities.

Equal Opportunity

Sobeys is committed to accommodating applicants with disabilities throughout the hiring process and will work with applicants requesting accommodation at any stage of this process.
Sobeys is committed to providing a compensation structure that is flexible, equitable and competitive in the market to enable performance and growth.
We may use Artificial Intelligence (AI) tools to support efficiencies in the candidate screening, assessment, and recruitment processes. These AI tools do not make hiring decisions on behalf of the Company. Hiring decisions are made by our Hiring Teams.
Sobeys is committed to creating accessible and inclusive hiring processes. We will work with applicants requesting accommodation at any stage of the recruitment process.