Azure Machine Learning

We are looking for a talented and experienced Azure Machine Learning Engineer to design, develop, and deploy scalable machine learning solutions on the Microsoft Azure platform. The ideal candidate will have strong expertise in MLOps, model development, data pipelines, and a solid understanding of various machine learning algorithms. This role is crucial for leveraging AI capabilities to solve complex business problems and drive data-driven decision-making.

Roles and Responsibilities:

• Design, develop, and deploy machine learning models using Azure Machine Learning services, including Azure ML Studio, Azure Databricks, and Azure Kubernetes Service (AKS).
• Build and manage robust MLOps pipelines for model training, validation, deployment, monitoring, and retraining.
• Implement data ingestion and transformation pipelines to prepare data for machine learning models, utilizing Azure Data Factory, Azure Synapse Analytics, or other relevant Azure data services.
• Collaborate with data scientists to translate models from research environments into production-ready solutions.
• Optimize model performance and efficiency, ensuring scalability and reliability in a production environment.
• Monitor deployed models for performance drift, data drift, and accuracy, implementing retraining strategies as needed.
• Manage Azure Machine Learning workspaces, compute resources, datasets, and experiments.
• Implement security best practices for data and models within the Azure environment.
• Automate machine learning workflows from data preparation to model serving.
• Troubleshoot and debug issues related to ML models and their deployment.
• Document solution designs, architectures, and operational procedures.
• Stay updated with the latest advancements in Azure ML services, machine learning algorithms, and MLOps best practices.

Required Skills and Qualifications:

• Strong experience with Microsoft Azure Machine Learning platform and services.
• Proficiency in Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with MLOps principles and tools for continuous integration and continuous delivery (CI/CD) of ML models.
• Solid understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning).
• Experience with Azure data services such as Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, or Azure SQL Database.
• Familiarity with Docker and Kubernetes for containerization and orchestration of ML models.
• Knowledge of version control systems (e.g., Git).
• Strong analytical, problem-solving, and debugging skills.
• Excellent communication skills (written and verbal) and ability to collaborate with cross-functional teams.
• Experience with other cloud platforms (AWS, GCP) or big data technologies is a plus.