Senior ML Engineer: Azure ML Production & Pipelines Lead

Blanc Labs; Colombia; A distancia; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

Blanc Labs in North America seeks a Senior Machine Learning Engineer to lead end-to-end ML model development on Azure. You will own data prep, feature engineering, training, evaluation, and deployment of scalable models as APIs for downstream systems.

Collaborate with data scientists and principal AI engineers to align models with architecture, monitor performance, and drive continuous improvement within a Microsoft-centric stack.

Formación

• Production deployment experience on Microsoft Azure
• Python and ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Hands-on with AML Studio/SDK/CLI v2, endpoints, pipelines, model registry
• Experience with Azure Data Lake Storage / Azure SQL
• Strong software engineering fundamentals; .NET or C# familiarity
• Collaborate with cross-functional teams in a Microsoft-centric enterprise environment

Responsabilidades

• Design, build, and deploy end-to-end ML models in Azure ML
• Own the full ML lifecycle: data prep, feature engineering, training, evaluation
• Collaborate with Data Scientists to identify high-impact ML opportunities
• Package models as scalable APIs for consumption by AI Engineers
• Maintain ML pipelines with AML Pipelines and DevOps integration
• Monitor production model performance with Azure Monitor

Conocimientos

Python

Azure ML

TensorFlow

PyTorch

scikit-learn

MLOps

API development

Azure Functions

Azure Databricks

Herramientas

Azure ML Studio

Azure DevOps

Azure Kubernetes Service

Azure Data Lake

Databricks

Descripción del empleo

Blanc Labs in North America seeks a Senior Machine Learning Engineer to lead end-to-end ML model development on Azure. You will own data prep, feature engineering, training, evaluation, and deployment of scalable models as APIs for downstream systems.

Collaborate with data scientists and principal AI engineers to align models with architecture, monitor performance, and drive continuous improvement within a Microsoft-centric stack.