Back to All Positions
Senior Machine Learning Engineer
Data & AIHybridFull-timeID: REQ-43658
N2P Systems
Toronto, ON, Canada5-8 years$110K - $110K CADPosted 2 weeks ago
Role Overview
## Role Overview
The Senior Machine Learning Engineer will support the AI CoE's Machine Learning and Data Science initiatives by building, deploying, and operationalizing end-to-end machine learning solutions in cloud environments. The role is highly technical and hands-on, with ownership spanning data preparation, feature engineering, model development, production deployment, monitoring, and lifecycle management.
## Key Responsibilities
- Build and operationalize end-to-end machine learning solutions for enterprise use cases.
- Develop scalable ML pipelines covering data preparation, feature engineering, model development, deployment, and monitoring.
- Deploy and manage machine learning models in cloud environments using Azure ML, Databricks, MLflow, MLOps, and CI/CD practices.
- Take machine learning models from prototype through production deployment and ongoing operational support.
- Implement model monitoring and lifecycle management practices for production ML solutions.
- Integrate machine learning solutions into enterprise applications and operational workflows.
- Collaborate with data scientists and engineers to accelerate enterprise AI delivery from proof of concept through production.
## What We Are Looking For
- Strong hands-on experience building, deploying, and operationalizing machine learning solutions in cloud environments.
- Expert-level proficiency in Python and SQL.
- Deep practical experience with Azure ML, Databricks, MLflow, CI/CD pipelines, and MLOps.
- Proven ability to take ML models from prototype to production and support them throughout their lifecycle.
- Experience building scalable ML pipelines and production-grade ML services.
- Strong understanding of model deployment, monitoring, and production support.
- Ability to work independently while collaborating effectively with data scientists and engineers.
## Preferred & Bonus Experience
- Experience with Generative AI and LLM applications.
- Familiarity with agentic AI frameworks.
- Experience with GenAIOps practices, including evaluation, monitoring, deployment, and lifecycle management of GenAI solutions.
- Broader experience across cloud-native ML platforms and enterprise AI implementations.
Key Responsibilities
- Build and operationalize end-to-end machine learning solutions for enterprise use cases.
- Develop scalable ML pipelines covering data preparation, feature engineering, model development, deployment, and monitoring.
- Deploy and manage machine learning models in cloud environments using Azure ML, Databricks, MLflow, MLOps, and CI/CD practices.
- Take machine learning models from prototype through production deployment and ongoing operational support.
- Implement model monitoring and lifecycle management practices for production ML solutions.
- Integrate machine learning solutions into enterprise applications and operational workflows.
- Collaborate with data scientists and engineers to accelerate enterprise AI delivery from proof of concept through production.
- ## What We Are Looking For
- Strong hands-on experience building, deploying, and operationalizing machine learning solutions in cloud environments.
- Expert-level proficiency in Python and SQL.
- Deep practical experience with Azure ML, Databricks, MLflow, CI/CD pipelines, and MLOps.
- Proven ability to take ML models from prototype to production and support them throughout their lifecycle.
- Experience building scalable ML pipelines and production-grade ML services.
- Strong understanding of model deployment, monitoring, and production support.
- Ability to work independently while collaborating effectively with data scientists and engineers.
- ## Preferred & Bonus Experience
- Experience with Generative AI and LLM applications.
- Familiarity with agentic AI frameworks.
- Experience with GenAIOps practices, including evaluation, monitoring, deployment, and lifecycle management of GenAI solutions.
- Broader experience across cloud-native ML platforms and enterprise AI implementations.
Required Skills & Qualifications
- Strong proficiency and experience with Python
- Strong proficiency and experience with SQL
- Strong proficiency and experience with Azure ML
- Strong proficiency and experience with Databricks
- Strong proficiency and experience with MLflow
- Strong proficiency and experience with CI/CD
- Strong proficiency and experience with MLOps
- Strong proficiency and experience with Model Deployment
- Strong proficiency and experience with Model Monitoring
- Strong proficiency and experience with Machine Learning
- Strong proficiency and experience with Machine Learning Model Deployment
- Strong proficiency and experience with Machine Learning Monitoring
Target Tech Stack
PythonSQLAzure MLDatabricksMLflowCI/CDMLOpsModel DeploymentModel MonitoringGenerative AILLM ApplicationsAgentic AI FrameworksGenAIOpsMachine LearningData ScienceMachine Learning Model DeploymentMachine Learning MonitoringFeature EngineeringMachine Learning PipelinesCloud ML PlatformsProduction SupportLLMAgentic AI
Quick Details
- Location
- Toronto, ON, Canada
- Employment Type
- Full-time
- Work Arrangement
- Hybrid
- Experience Level
- 5-8 years
- Compensation
- $110K - $110K CAD
- Domain Focus
- Data & AI
- Requisition Ref
- REQ-43658
Ready to Apply?
Submit your resume and contact information. Our recruitment lead for this role will review your dossier and connect with you.
Apply for this Role