We have an exciting opportunity for a full‑timeMachine Learning Engineerto join our IT team inLangley, BC .Reporting to the Manager, Data & Analytics you will work closely with the Data Scientists and Data Engineers to help extract value from our data by leading all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.ResponsibilitiesBuilding and integrating end to end lifecycles of large‑scale, distributed machine learning systems using the latest open source and cloud technologies.Maintaining cloud workspaces and optimizing cloud compute resources.Building automated tests and validations for machine learning models and underlying data.Maintaining production machine learning model registry and building retraining strategies.Developing and implementing methods for detecting model and data drifts.Developing scalable tools and services for handling machine learning workflows.Implementing cloud distributed approaches for deep learning models.Collaborating with data scientists and data engineers to test and deploy ML models at scale.Identifying and testing the latest technological tools that can help improve the performance and maintenance of our machine learning systems.Identifying project requirements, tracking, and communicating project progress with peers, and driving projects to completion.Sharing knowledge through documentation and presentations to peers and senior leaders.Dealing with any unexpected pipeline production issues that might require an MLE intervention.QualificationsA Master’s or bachelor’s degree in computer science, applied mathematics,



or engineering.3+ years of experience in building end‑to‑end machine learning pipelines.Experience in MLOps to deploy and maintain machine learning models.Experience working with Large Language Models (LLMs) including prompt engineering, fine‑tuning and integrating LLM‑based solutions into production‑grade machine learning systems (nice to have).Experience building, managing, and deploying Databricks Asset Bundles (DABs) or similar infrastructure‑as‑code frameworks to package, version, and promote data and ML workloads across environments (nice to have).Experience building systems with scalable data processing technologies using Spark, Python, SQL.Experience in CI/CD and be able to follow standard workspace branching practices.Exposure to Databricks and associated tools like ML Flow and Delta Lake.Familiarity with data‑oriented workflow orchestration frameworks (Databricks Jobs, Azure Data Factory, Airflow etc.)Experience developing containers in cloud computing environments (Azure, AWS, GCloud, etc.)Exposure to machine learning and drift detection methodology and best practices.Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, etc.)Rigor in high code quality, automated testing, and other engineering best practices.Experience working with cloud computing and database systems.Fluency in one or more programming languages (Python, SQL, etc.)Experience with version control tools such as Git and Git workflows.You areCollaborative.Self‑motivated.Cutting-edge.Able to work independently while part of a team.Critical and analytical thinker.BenefitsIn addition to ahighly competitive salary, we offer a great range ofbenefits, acompany pension plan, free parking, exclusive team member offers, and opportunities for development and career progression.Compensation$94,552.00 - $118,190.00 The compensation offered for this position will take into consideration location, education, skills, experience and other factors.#J-18808-Ljbffr

📌 Machine Learning Engineer - $94,552 - $118,190 A Year (Winnipeg)
🏢 Pattison Food Group
📍 Winnipeg