We are looking for a Senior Machine Learning / MLOps Engineer to join an enterprise AI Center of Excellence (AI CoE) and help build, deploy, and operationalize production-grade machine learning solutions.

This is a hands-on engineering role for someone who can take ML solutions from prototype to production , build scalable pipelines, deploy and monitor models in cloud environments, and support the complete ML lifecycle.

You will work closely with data scientists and engineering teams to turn AI/ML initiatives into reliable, scalable enterprise solutions.

What You'll Do

- Design, build, deploy, and operationalize end-to-end machine learning solutions.
- Develop scalable ML pipelines covering data preparation, feature engineering, model development, deployment, and monitoring .
- Build and maintain production ML workflows using Azure ML, Databricks, MLflow, MLOps, and CI/CD .
- Take machine learning models from proof of concept through production deployment .
- Implement model monitoring, lifecycle management, and operational processes for production ML systems.
- Integrate ML solutions with enterprise applications and operational workflows.
- Troubleshoot and provide ongoing production support for ML pipelines and deployed models.
- Partner with data scientists and software/data engineers to accelerate enterprise AI delivery.




- Contribute to engineering standards and best practices for scalable and maintainable ML solutions.

What We're Looking For
- 5+ years of hands-on experience in machine learning engineering, ML platform engineering, MLOps, or a closely related field.
- Strong hands-on experience building and deploying production machine learning solutions .
- Expert-level proficiency in Python and SQL .
- Deep experience with Azure ML, Databricks, and MLflow .
- Robust understanding of MLOps and CI/CD pipelines .
- Practical experience with model deployment, monitoring, and lifecycle management .
- Proven experience taking ML models from prototype to production .
- Experience developing scalable ML pipelines and production-grade ML services.
- Experience working with cloud-based ML platforms and enterprise data/AI environments.
- Ability to work independently and collaborate effectively with data scientists and engineers.

Nice to Have
- Experience with Generative AI and LLM applications .
- Experience with agentic AI frameworks .
- Knowledge of GenAIOps , including evaluation, monitoring, deployment, and lifecycle management of GenAI solutions.
- Experience supporting enterprise AI/ML platforms in production.

📌 Senior Machine Learning / MLOps Engineer (Toronto)
🏢 N2P Systems
📍 Toronto