Job Title: Senior Machine Learning Engineer Location: Toronto, ON Work Arrangement: Hybrid Employment Type: Full-Time FTE Job Summary We are seeking an experienced Senior Machine Learning Engineer to support the AI Center of Excellence (AI CoE) across Machine Learning and Data Science initiatives.

The ideal candidate will have strong hands-on experience designing, building, deploying, and operationalizing machine learning solutions in cloud environments.

The candidate should have expert-level Python and SQL skills along with strong experience in Azure ML, Databricks, MLflow, MLOps, CI/CD, model deployment, monitoring, and machine learning lifecycle management .

This is a highly technical and hands-on role focused on taking machine learning solutions from proof of concept through production deployment and ongoing operational support.

Key Responsibilities Design, develop, deploy, and operationalize scalable machine learning solutions.

Build end-to-end ML solutions covering data preparation, feature engineering, model development, deployment, monitoring, and production support.

Develop scalable machine learning pipelines and services for enterprise applications.

Take machine learning models from prototype/POC through validation, production deployment, and lifecycle management.

Build and maintain automated ML pipelines using contemporary MLOps practices.

Implement CI/CD pipelines and automated deployment processes for machine learning applications and models.

Deploy and manage machine learning models using cloud-native ML platforms.

Implement model monitoring, performance tracking, drift detection, and ongoing model maintenance.





Integrate machine learning models and services into enterprise applications and operational workflows.

Collaborate with Data Scientists, Data Engineers, Software Engineers, and business stakeholders to deliver enterprise AI solutions.

Provide production support and troubleshoot issues related to ML pipelines, models, deployments, and cloud infrastructure.

Establish and follow best practices for model versioning, experiment tracking, deployment, monitoring, and lifecycle management.

Contribute to the development and adoption of MLOps and machine learning engineering standards across the AI CoE.

Required Technical Skills Strong hands-on experience with Python for machine learning engineering and automation.

Expert-level SQL skills.

Strong experience with Machine Learning Engineering and MLOps .

Hands-on experience with Azure Machine Learning (Azure ML) .

Strong experience with Databricks .

Hands-on experience with MLflow for experiment tracking, model management, and lifecycle management.

Strong understanding of CI/CD pipelines and automated deployment processes.

Experience with model deployment, monitoring, versioning, and lifecycle management .

Experience building scalable ML pipelines and production-grade ML services .





Strong understanding of cloud-native machine learning architectures and production environments.

Proven experience moving machine learning models from prototype/POC to production . MLOps & Production Engineering Experience implementing end-to-end MLOps workflows.

Experience with model packaging, deployment, monitoring, and maintenance.

Experience implementing automated testing and deployment for ML solutions.

Experience with production monitoring and troubleshooting of ML applications.

Understanding of model performance monitoring, data/model drift, and retraining workflows.

Experience integrating ML solutions with enterprise applications, APIs, and operational workflows.

Preferred / Nice-to-Have Skills Experience with Generative AI and Large Language Model (LLM) applications .

Experience with Agentic AI frameworks and AI agent architectures.

Experience implementing GenAIOps practices.

Experience with GenAI evaluation, monitoring, deployment, and lifecycle management.

Experience operationalizing LLM-based applications in enterprise environments.

Qualifications Proven experience as a Machine Learning Engineer, Senior ML Engineer, MLOps Engineer, or similar role .

Strong experience delivering production-grade machine learning solutions in enterprise environments.

Demonstrated ability to work independently on complex technical problems.

Strong collaboration skills with Data Scientists, Data Engineers, Software Engineers, and business stakeholders.

Strong understanding of the complete machine learning lifecycle, from experimentation and development through production deployment and monitoring.

📌 Senior Machine Learning Engineer || Toronto, ON - Onsite || Fulltime FTE
🏢 AceStack
📍 Toronto