Senior Machine Learning Engineer

Role: Senior Machine Learning Engineer Location: Toronto, ON Work Model: Hybrid Experience: 10+ Role Overview We are seeking an experienced Senior Machine Learning Engineer to support the AI CoE’s Machine Learning and Data Science initiatives. The ideal candidate will have strong hands-on expertise in designing, developing, deploying, and operationalizing end-to-end machine learning solutions in cloud environments. This is a highly technical and hands-on role focused on taking ML solutions from proof of concept to production, building scalable ML pipelines and services, and supporting models throughout their production lifecycle. Key Responsibilities • Design, develop, deploy, and operationalize end-to-end machine learning solutions in cloud environments. • Perform data preparation, feature engineering, model development, validation, deployment, monitoring, and production support. • Build scalable and reusable ML pipelines and services for enterprise AI applications. • Develop and maintain machine learning solutions using Python and SQL. • Leverage Azure ML, Databricks, and MLflow for model development, experiment tracking, deployment, and lifecycle management. • Implement MLOps practices, including model versioning, automated deployment, CI/CD, monitoring, and governance. • Build and maintain automated CI/CD pipelines for machine learning workloads and production deployments. • Deploy ML models and services using cloud-native architectures and enterprise deployment practices. • Monitor model performance, data quality, system health, and production workloads; troubleshoot and resolve issues as required. • Collaborate with Data Scientists, Data Engineers, Software Engineers, and business stakeholders to deliver production-ready AI solutions. • Help establish and improve standards for ML engineering, deployment, monitoring, and lifecycle management across the AI CoE. • Support the transition of ML prototypes and proof-of-concepts into scalable, reliable, production-grade solutions. • Contribute to production support, continuous improvement, and optimization of deployed ML solutions. Required Skills & Experience • Strong hands-on experience as a Machine Learning Engineer / ML Engineer delivering production ML solutions. • Expert-level proficiency in Python and SQL. • Strong experience with Azure Machine Learning (Azure ML). • Hands-on experience with Databricks and MLflow. • Strong understanding of MLOps, ML lifecycle management, model deployment, and monitoring. • Experience building and managing CI/CD pipelines for machine learning applications. • Proven experience taking machine learning models from prototype/POC through production deployment. • Strong understanding of data preparation, feature engineering, model development, validation, deployment, and production support. • Experience building scalable ML pipelines and cloud-native ML services. • Strong understanding of cloud-based machine learning architectures and enterprise application integration. • Ability to work independently while collaborating effectively within cross-functional engineering and data science teams. Nice to Have • Experience with Generative AI and Large Language Models (LLMs). • Hands-on experience with Agentic AI frameworks and LLM-based applications. • Knowledge of GenAIOps, including evaluation, monitoring, deployment, observability, and lifecycle management of GenAI solutions. • Experience integrating AI/ML solutions into enterprise applications and operational workflows. • Experience with model governance, responsible AI, and enterprise AI standards.