Job Details Job Title:Senior AI/ML Platform EngineerLocation:Toronto, ON (Hybrid - 2 days in office)Job Type:Contract (6 months to start - extendable)Job Summary For our Technology Advisory Services division, we are seeking a highly skilled and experiencedSenior AI/ML Platform Engineerto lead the design, development, and implementation of scalable MLOps pipelines onAzureandDatabricks . This role will focus on optimizing the lifecycle of machine learning models — from development to deployment and monitoring — while ensuring high availability, performance, and security.Key ResponsibilitiesDesign and implement end-to-end MLOps pipelines using Azure Machine Learning, Databricks, MLflow, and related tools.Collaborate with Data Scientists, Engineers, and DevOps teams to automate model training, validation, deployment, and monitoring processes.Build scalable data pipelines and integrate feature engineering workflows in Databricks.Set up model versioning, testing, and CI/CD workflows for ML artifacts.Ensure security, compliance, and governance standards are met across all ML operations.Monitor and troubleshoot ML services in production, and proactively enhance performance and reliability.Required QualificationsBachelor’s or Master’s degree in Computer Science, Engineering, or a related field.5+ years of experience in software engineering, data engineering, or DevOps with at least 2+ years in MLOps roles.Strong hands-on experience withAzure servicessuch as Azure Machine Learning, Azure DevOps, Azure Data Lake, and Azure Kubernetes Service (AKS).Expertise inDatabricks(including Delta Lake, MLflow, and notebooks).Experience withML model deployment, monitoring, and governance in a cloud-native environment.Experience withFeature EngineeringProficient in Python and familiar with libraries like scikit-learn, pandas, and TensorFlow or PyTorch.Experience with CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, Jenkins).Familiarity with infrastructure as code (e.g., Terraform, ARM templates).Strong Communication skills / Stakeholder management skills , someone who can face off with business stakeholders on the data science sidePreferred QualificationsDatabricks Certified Professional or Microsoft Azure Certification.Experience with containerization ( Kubernetes ) and orchestration tools.Understanding of responsible AI principles and model explainability tools.#J-18808-Ljbffr