Machine Learning Analyst
Explicitly mentions "vibe coding" and emphasizes agentic LLMOps work with Langgraph and rapid engineering of agentic systems.
About the Role
Join Sobeys' MLOps Engineering team in Toronto to design, build, and maintain end-to-end MLOps and agentic LLMOps systems. You will develop Langgraph-based agents, scalable PySpark data pipelines in Databricks, and production ML deployment and monitoring solutions to deliver AI-driven retail features.
Job Description
Role
Sobeys is hiring a Machine Learning Analyst / MLOps Engineer to the MLOps Engineering team in the Enterprise Data and Advanced Technologies unit. The role focuses on designing, building, maintaining, and improving end-to-end MLOps and agentic LLMOps solutions that deliver measurable business value in a retail environment.
Team & Location
Position is based at the Sobeys COLAB Office (Toronto Downtown) within the MLOps Engineering team of Advanced Technologies.
Key Responsibilities
- Design, develop, deploy, and maintain MLOps and LLMOps engineering systems and automated workflows for training, testing, deployment, and monitoring of ML models.
- Build Langgraph-based agentic applications that integrate LLMs and external tools to automate and optimize business tasks.
- Develop scalable data processing pipelines using PySpark (including UDFs) and tune performance across distributed systems, primarily within the Databricks ecosystem.
- Write maintainable, modular, object-oriented Python code following production-grade design patterns.
- Research and translate complex business processes into technical AI solutions with measurable impact.
- Collaborate cross-functionally with data scientists, data engineers, analysts, product managers, and business stakeholders.
- Learn and deliver agentic solutions within the Snowflake environment as required.
Requirements
- Bachelor’s degree or higher in Computer Science, Software Engineering, Data Science, or related field; LLMOps engineering certifications are an asset.
- Proven implementation experience with MLOps and LLMOps systems.
- 1+ years of industry experience in Object-Oriented Python development with production-grade software design patterns.
- 1+ years of industry experience with Spark (PySpark or Scala) building efficient data pipelines and optimized UDFs.
- 1+ years of experience maintaining and debugging production ML pipelines.
- Proficiency with MLOps tools and frameworks (example: MLflow).
- Solid understanding of vector databases (examples: FAISS, Pinecone, Weaviate) and LLM retrieval techniques such as RAG.
- Experience deploying LLMs or fine-tuned models in production is an asset.
- Familiarity with cloud platforms (AWS, GCP, Azure, Databricks) is strongly recommended.
- Strong communication skills and proven ability to manage multiple stakeholders and priorities in fast-paced environments.
Benefits & Notes
- Eligible teammates may receive health and dental benefits, retirement and savings programs including an Employee Share Ownership Plan, virtual healthcare, Employee and Family Assistance Program, learning and development opportunities, parental leave top-up, paid vacation, and a 10% in-store discount at participating banners.
- Sobeys is committed to accommodation for applicants with disabilities and may use AI tools to support hiring processes (AI does not make hiring decisions).
Other
- Candidates must be legally authorized to work and provide documentation during onboarding.
- Agency submissions and unsolicited resumes are not requested.