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Senior Machine Learning Engineer

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Hybrid

Senior Machine Learning Engineer

N2P Systems

Senior Machine Learning Engineer

Skills

SQL QueriesPythonData ScienceDatabricksMachine LearningAIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Toronto, ON, Canada

Work mode:

Hybrid

Published on:

17 October 2026

What they need


Data & AIHybridFull-timeID: REQ-43658

N2P Systems

Toronto, ON, Canada 5-8 years $110K - $110K CAD Posted 1 month ago

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.

Required Skills & Qualifications

  • 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.
  • 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.

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

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