Senior Machine Learning Engineer
Blanc Labs5 months ago
Remote, WorldwideSenior
Responsibilities
- Design, build, deploy, and manage end-to-end machine learning models using proprietary datasets and Azure Machine Learning.
- Own data preparation, feature engineering, model training, evaluation, validation, versioning, retraining, and continuous improvement.
- Collaborate with Data Scientists, Principal AI Engineers, and data engineering teams to identify opportunities and align models with Azure architecture and engineering practices.
- Package and expose trained models as scalable APIs using Azure Functions, Azure App Service, or Azure Kubernetes Service.
- Build and maintain model pipelines using Azure ML Pipelines and Azure DevOps.
- Monitor production model performance with Azure Monitor and Application Insights and troubleshoot model drift, data quality issues, and performance bottlenecks.
- Integrate models with Azure data platforms and Microsoft-native AI services, including Azure Synapse, Azure Data Factory, Azure Databricks, Azure OpenAI Service, and Azure AI Studio.
Requirements
- Strong experience in machine learning engineering with production deployment experience on Microsoft Azure.
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Hands-on experience with Azure Machine Learning, including AML Studio, AML SDK/CLI v2, endpoints, pipelines, and model registry.
- Experience with data preprocessing, feature engineering, and model evaluation using Azure Databricks and/or Azure Synapse Analytics.
- Experience deploying machine learning models as APIs or microservices using Azure Functions, App Service, or Azure Kubernetes Service.
- Familiarity with Azure MLOps practices, model versioning, Azure DevOps CI/CD, monitoring, and retraining pipelines.
- Experience with large-scale or proprietary datasets stored in Azure Data Lake Storage or Azure SQL.
- Strong software engineering fundamentals in testing, scalability, and performance optimization; familiarity with .NET or C# is an asset.
- Ability to collaborate effectively in a Microsoft-centric enterprise environment.
- Experience with Azure OpenAI Service, Azure AI Studio, Azure Cognitive Services, Docker, Azure Kubernetes Service, Event Hubs, Stream Analytics, LLMs, hybrid AI/ML systems, Microsoft Copilot, Azure Data Factory, Synapse Pipelines, Databricks workflows, Power BI, or Power Automate is a plus.
- Microsoft certifications such as Azure AI Engineer Associate, Azure Data Scientist Associate, or Azure Solutions Architect are considered a plus.
Benefits
- Equal opportunity employment under the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act.
- Reasonable accommodations are available for candidates with a disability or medical need during the recruitment process.
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