Summary
✨ AI‑Generated
A senior machine learning engineering role focused on designing, deploying, and supporting scalable AI solutions. Responsibilities include ML pipelines, cloud deployment, monitoring, and collaboration with data professionals.
Highlights
Senior AI engineering opportunity to build enterprise ML solutions, manage model lifecycles, and collaborate across data and technology teams.
Description
Position: Senior Machine Learning Engineer
Location: Toronto, On (Hybrid)
Employment Type: Full-Time
Experience Required: 8 + Years
Position Overview:
We are seeking a highly skilled Senior Machine Learning Engineer to design, build, deploy, and support scalable machine learning solutions for enterprise AI initiatives.
Key Responsibilities:
Develop and operationalize end-to-end ML solutions, from data preparation and feature engineering to model deployment and production support.Build, automate, and maintain ML pipelines using Azure ML, Databricks, MLflow, and MLOps best practices.Deploy, monitor, troubleshoot, and optimize machine learning models in cloud environments.Implement CI/CD pipelines for ML workflows and ensure reliable model lifecycle management.Collaborate with Data Scientists, Data Engineers, and business stakeholders to accelerate AI solution delivery.Support model monitoring, performance tracking, retraining, and governance activities.Contribute to scalable AI platform development and integration with enterprise applications.
Required Skills:
7+ years of experience in Machine Learning Engineering, Data Science, or related fields.Strong expertise in Python, SQL, Machine Learning, Azure ML, Databricks, MLflow, and MLOps.Hands-on experience with model deployment, monitoring, CI/CD pipelines, and cloud-native ML platforms.Proven track record of moving ML models from prototype to production.Experience building scalable data and ML services in enterprise environments.Strong problem-solving, collaboration, and communication skills.Experience with Generative AI, Large Language Models (LLMs), Agentic AI frameworks, and GenAIOps.Knowledge of AI evaluation, monitoring, governance, and lifecycle management for Gini applications.
