Title - Senior MLOps Engineer – Azure AI & Agentic AI Employment Type - Contract Contract Duration - 12 months Work Mode - 100% Remote Location - Anywhere in Canada Pay Rate - 70$/hr on INC.

Required Skills (Maximum of 6) MLOps and Machine Learning Lifecycle: Solid experience managing the full MLOps lifecycle, including model development, experimentation, validation, deployment, monitoring, retraining, and governance.

Programming and Machine Learning Frameworks: Proficiency in Python, Pandas, scikit-learn, MLflow, PySpark, and Tensor

Flow.

Azure AI and Data Services: Hands-on experience with Azure Machine Learning, Azure Databricks, Azure Data Factory, Azure Functions, Azure OpenAI, and Azure AI Search.

Model Deployment and Dev

Ops: Experience deploying and scaling ML models using Azure Kubernetes Service (AKS), with CI/CD pipelines built using Azure Dev

Ops and/or Git

Hub Actions.

Generative AI and Agentic AI: Experience with large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), agentic AI, and AI observability.

Model Monitoring and Governance: Experience with model performance monitoring, data drift detection, automated ML testing, model governance, cloud cost optimization, and strong problem-solving, documentation, and cross-functional communication skills.

Fluency in both English and French is required.

Nice-to-Have Skills (Maximum of 3)



Experience implementing enterprise-scale generative AI and agentic AI solutions using Azure OpenAI and Azure AI Search.

Experience building automated model retraining, drift detection, and end-to-end MLOps workflows.

Experience optimizing cloud infrastructure, model serving performance, scalability, and operational costs.

Key Responsibilities Design, develop, and maintain end-to-end MLOps pipelines covering data preparation, model training, validation, deployment, monitoring, and retraining.

Build and operationalize machine learning models using Python, scikit-learn, Tensor

Flow, PySpark, and MLflow.

Develop and manage Azure-based AI and data solutions using Azure Machine Learning, Databricks, Data Factory, Azure Functions, Azure OpenAI, and Azure AI Search.

Deploy, scale, and manage machine learning models and AI applications using AKS and automated CI/CD pipelines.

Develop generative AI and agentic AI solutions using LLMs, prompt engineering, RAG, and appropriate AI orchestration patterns.

Implement model monitoring, data drift detection, automated testing, observability, and model governance practices.

Optimize model performance, cloud resource utilization, scalability, reliability, and operational costs.

Maintain technical documentation and collaborate with engineering, data science, architecture, and business teams.

Communicate technical solutions and project updates effectively in both English and French.

📌 Senior MLOps Engineer Azure AI & Agentic AI (Toronto)
🏢 Artech
📍 Toronto