Senior Machine Learning Engineer

Senior Machine Learning Engineer

Blanc Labs is a premier partner for global enterprises, leading the way in digitization, automation, and the development of next-generation digital products and services. Our expertise in digital transformation powers businesses to accelerate service delivery, drive customer engagement, and foster growth.

We are looking for a Senior Machine Learning Engineer to lead the end-to-end development and lifecycle management of machine learning models powered by proprietary data, within a Microsoft-centric technology environment. This is a highly impactful role at the core of our AI ecosystem, responsible for building scalable, production-grade ML systems on Azure that directly power intelligent product features.

Key Responsibilities

• Design, build, and deploy end-to-end machine learning models using proprietary datasets, primarily within Azure Machine Learning
• Own the full ML lifecycle, including data preparation, feature engineering, model training, evaluation, and validation
• Collaborate with Data Scientists to identify and prioritize high-impact ML opportunities
• Work with Principal AI Engineers to ensure models align with system architecture and engineering best practices across the Azure ecosystem
• Package and expose trained models as scalable APIs (Azure Functions, Azure App Service, or AKS) for consumption by AI Engineers and downstream systems
• Build and maintain model pipelines using Azure ML Pipelines / Azure DevOps, including versioning, retraining, and continuous improvement workflows
• Monitor model performance in production using Azure Monitor and Application Insights, ensuring accuracy, reliability, and relevance over time
• Troubleshoot model drift, data quality issues, and performance bottlenecks
• Partner with data engineering teams working in Azure Synapse, Azure Data Factory, and Azure Databricks to ensure clean, reliable data pipelines feeding ML workflows
• Support integration of models with Microsoft-native AI services, including Azure OpenAI Service and Azure AI Studio, where applicable

Qualifications

• Strong experience in machine learning engineering, with production deployment experience on Microsoft Azure
• Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
• Hands-on experience with Azure Machine Learning (AML Studio, AML SDK/CLI v2, endpoints, pipelines, model registry)
• Experience with data preprocessing, feature engineering, and model evaluation techniques, using Azure Databricks and/or Azure Synapse Analytics
• Hands-on experience deploying ML models as APIs or microservices using Azure-native compute (Azure Functions, App Service, or Azure Kubernetes Service)
• Familiarity with MLOps practices on Azure, including model versioning (AML Model Registry), CI/CD via Azure DevOps, monitoring, and retraining pipelines
• Experience working with large-scale or proprietary datasets stored in Azure Data Lake Storage / Azure SQL
• Strong software engineering fundamentals (testing, scalability, performance optimization) with familiarity in.NET or C# environments an asset given the broader Microsoft stack
• Ability to collaborate effectively with cross-functional teams in a Microsoft-centric enterprise environment

Nice-to-Have

• Experience with Azure OpenAI Service, Azure AI Studio, or Azure Cognitive Services
• Familiarity with containerization and orchestration tools (Docker, Azure Kubernetes Service )
• Experience with real-time or low-latency ML systems on Azure (Event Hubs, Stream Analytics)
• Exposure to LLMs or hybrid AI/ML systems, particularly via Azure OpenAI or Microsoft Copilot ecosystem
• Experience building data pipelines with Azure Data Factory, Synapse Pipelines, or Databricks workflows
• Microsoft certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate, Azure Solutions Architect) considered a plus
• Exposure to Power Platform (Power BI, Power Automate) for surfacing ML outputs to business stakeholders

Blanc Labs is an equal opportunity employer and is committed to employing in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act. Accommodations within reason due to a disability or medical need are available on request for candidates taking part in the recruitment process.