Senior MLOps Engineer – Azure AI & Agentic AI

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: Strong 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 TensorFlow.
• 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 DevOps: Experience deploying and scaling ML models using Azure Kubernetes Service (AKS), with CI/CD pipelines built using Azure DevOps and/or GitHub 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, TensorFlow, 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.