Location: Sobeys COLAB Office (Toronto Downtown)

Team: MLOps Engineering, Enterprise Data and Advanced Technologies

Overview

The MLOps Engineering team of Advanced Technologies, part of Enterprise Data and Advanced Technologies unit at Sobeys operates on the frontlines of retail innovation. At Advanced Technologies, 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 behavior 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 MLOps and expertise in building Langgraph based Agentic LLMOps agentic systems, has experience in Object-Oriented Python and scale for pyspark learning in Databricks echo system. In this role, you will deliver, maintain and improve end-to-end MLOps/Agentic solutions, research complex business processes, and build intelligent systems that are scalable, maintainable, and impactful.

Key Responsibilities:

• We love vibe coding, but we need MLOps Engineer who is strong on engineering and passionate on agentic development inherently! Need to be able to build, maintain MLOps/LLMOps engineering systems with passion.
• Business Process Research: Analyze and translate complex business operations into technical AI solutions with measurable value.
• Agent Development (Langgraph): Build and maintain Langgraph-based agentic applications using LLMs and tool integrations to automate and optimize business tasks.
• MLOps & LLMOps: Build and maintain automated workflows for training, testing, deployment, and monitoring of ML models using industry-standard MLOps and LLMOps tools.
• 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.
• 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.
• Eager to learn the Snowflake environment and deliver business-facing agentic solutions within that platform.
• Absolute team player with eager to learn and contribute!

What you should bring to the team:

• Bachelor's or above degree in Computer Science, Software Engineering, Data Science - LLMOps engineering certifications.
• Proven implementation experience with MLOps engineering systems, LLMOps systems.
• 1+ years of industry level expertise in Object-Oriented Python development with production-grade software design patterns in the industry.
• 1+ years of industry level experience with Spark (using 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
• Proficiency in MLOps tools and frameworks (e.g., MLflow).
• 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.

Total Rewards

We offer a Total Rewards package designed to support teammates at work and in life. Depending on role and eligibility, teammates may receive health and dental benefits, retirement and savings programs including an Employee Share Ownership Plan, a 10% in-store discount at participating banners, virtual healthcare and an Employee and Family Assistance Program, learning and development opportunities, parental leave top-up, and paid vacation.

Sobeys is committed to providing a compensation structure that is flexible, equitable and competitive in the market to enable performance and growth. To learn more about this opportunity including the expected range of compensation in accordance with Pay Transparency Legislation where required please click the "I'm interested" or "Apply" button above. Individual compensation is determined based on qualifications, experience, and internal equity within the range provided.

Additional Information

External websites may share our organization's job postings which includes compensation information based on similar roles and market benchmarks. These figures are provided for general comparison purposes only and are not issued or verified by our organization.

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.